CN120970817B - Multispectral calibration method, multispectral calibration device and multispectral calibration storage medium for imaging colorimeter - Google Patents

Abstract

This application discloses a multispectral calibration method, apparatus, and storage medium for an imaging colorimeter, used to improve the accuracy of optical inspection of a display screen. The calibration system includes an integrating sphere light source, controlled to achieve a target brightness; the detection temperature of the calibration system is adjusted to reach the target temperature; the light source at the exit port of the integrating sphere light source undergoes band separation processing to generate several discrete bands; band images corresponding to the discrete bands are acquired; spectral radiation data of the integrating sphere light source in different discrete bands are obtained; the flat-field correction coefficient matrix and brightness calibration coefficient for each discrete band are calculated based on the band images and spectral radiation data; brightness response data is generated based on band images acquired at different temperatures; a temperature coefficient is generated based on brightness response data at a reference temperature and a contrast temperature; and brightness response compensation is performed on the band images based on the flat-field correction coefficient matrix, brightness calibration coefficient, and temperature coefficient.

Description

A multispectral calibration method, device, and storage medium for an imaging colorimeter.

Technical Field

This application relates to the field of display screen testing, and in particular to a multispectral calibration method, apparatus and storage medium for an imaging colorimeter.

Background Technology

With technological innovation, new display technologies (such as MicroLED and flexible foldable screens) are rapidly reshaping the industry landscape. As a core link in the display screen industry chain, display screen quality testing technology continues to receive attention. Testing the brightness and color uniformity of micron-level pixels on the display screen surface has become a key factor determining the quality of display screen products. Currently, the optical characteristics testing of display screens mainly employs a combination of imaging colorimeters and spectrometers. This involves collecting and analyzing the light emitted by the display screen to obtain parameters such as brightness and colorimetry.

However, with the continuous updates in display technology, the structure of new displays is becoming increasingly complex, the arrangement of pixels is becoming more precise, and with the continuous expansion of display application fields, the structure of displays is constantly changing. For example, flexible screens, foldable screens, curved screens, splicing screens, AR screens, etc. More and more new types of displays are emerging. Different new displays have different special structures. For example, flexible screens have extension structures, foldable screens have folding areas, and splicing screens have splicing edges. These special structures are used to complete their functionality in specific fields.

As the precision of new displays gradually improves, existing calibration techniques face numerous challenges. Due to the unique structure of these displays, individual brightness and color uniformity testing of specific structures is often required. The display technology of these new displays is highly precise, especially the technology specific to their unique structures, which is unique to this type of display. This necessitates the use of different discrete spectral bands in the calibration system. However, existing calibration methods are mostly designed for specific bands or fixed light source conditions, lacking comprehensive calibration capabilities across the entire multispectral band. In other words, existing calibration methods are insufficient to meet the spectral characteristics testing requirements of new displays. Furthermore, in multispectral discrete band calibration, flat-field correction and brightness calibration are crucial data points. However, existing calibration techniques often treat flat-field correction and brightness calibration as separate processes, lacking a systematic integration method, resulting in significant differences in their calibration outcomes. Secondly, the calibration of new displays often requires the introduction of external light sources with specific discrete bands and specific manipulations of the display's unique structure to test the brightness and color uniformity of the specific structure during operation. This necessitates calibration under more complex ambient lighting conditions. Conventional calibration and testing equipment struggles to maintain stable measurement accuracy because the more conditions introduced, the more environmental factors cause drift in the calibration and testing system, leading to deviations in the calibration response data. This is particularly true for ambient temperature and the internal temperature of the colorimeter, which in turn affect the calibration results and compromise the reliability of the measurements. Furthermore, existing calibration methods are incompatible with the display technologies of new displays, reducing the accuracy of optical testing of these displays.

Summary of the Invention

This application discloses a multispectral calibration method, apparatus, and storage medium for an imaging colorimeter, used to improve the accuracy of optical inspection of a display screen.

In a first aspect, embodiments of this application provide a multispectral calibration method for an imaging colorimeter, comprising:

An integrating sphere light source is set up in the calibration system and controlled to achieve the target brightness. The calibration system includes an imaging colorimeter and a band separation module. The detection temperature of the calibration system is adjusted to reach the target temperature, which includes a reference temperature and several comparison temperatures. The band separation module performs band separation processing on the light source at the exit of the integrating sphere light source to generate several discrete bands. The imaging colorimeter acquires band images corresponding to all discrete bands. The spectral radiation data of the integrating sphere light source in different discrete bands are obtained. The flat-field correction coefficient matrix and brightness calibration coefficient of each discrete band are calculated based on the band images and corresponding spectral radiation data. The corresponding brightness response data are generated based on the band images acquired at different temperatures. The temperature coefficient is generated based on the brightness response data at the reference temperature and the comparison temperature. The brightness response of the band images is compensated based on the flat-field correction coefficient matrix, the brightness calibration coefficient, and the temperature coefficient.

Optionally, the calibration system may also include a spectrophotometer;

The steps for acquiring spectral radiance data of an integrating sphere light source in different discrete bands include:

The spectral radiation intensity distribution at the center of the integrating sphere light source outlet was detected using a spectrophotometer; the standard radiation intensity value at the center wavelength of each discrete band was detected using a spectrophotometer.

Optionally, the steps of calculating the flat-field correction coefficient matrix and brightness calibration coefficients for each discrete band based on the band image and spectral radiometric data include:

When the spectral radiation intensity distribution does not meet the brightness uniformity condition, adjust the operating parameters of the integrating sphere light source until the spectral radiation intensity distribution meets the brightness uniformity condition; when the spectral radiation intensity distribution meets the brightness uniformity condition, generate a flat field correction coefficient matrix based on the brightness mean of the band image and the brightness value of the pixel; generate a brightness calibration coefficient based on the brightness mean of the band image and the standard radiation intensity value corresponding to the discrete band.

Optionally, the step of generating brightness response data based on band images acquired at different temperatures includes:

Obtain the average brightness data of band images acquired at different temperatures; generate brightness response data based on the average brightness data, flat field correction coefficient matrix, and brightness calibration coefficient.

Optionally, adjusting the detection temperature of the calibration system to reach the target temperature includes the following steps:

The colorimeter generates internal temperature parameters using an internal temperature sensor and ambient temperature parameters using an ambient temperature sensor. The current detection temperature is then generated based on the colorimeter's thermal coupling factor, thermal time factor, internal temperature parameters, and ambient temperature parameters. If the detection temperature does not reach the target temperature range, the ambient temperature and/or the colorimeter's internal temperature are adjusted until the detection temperature meets the target. Once the detection temperature reaches the target temperature range, the calibration system is confirmed to have reached the target temperature.

Optionally, after the step of performing brightness response compensation on the band image based on the flat field correction coefficient matrix, brightness calibration coefficient, and temperature coefficient, the multispectral calibration method further includes:

Set the automatic calibration cycle and automatic calibration change rate, and use the built-in standard light source to calibrate the calibration system; during the calibration process, calculate the drift coefficient based on the currently measured brightness response data and the initially calibrated brightness response data; use the drift coefficient for subsequent brightness response compensation.

Optionally, after the steps of calculating the flat-field correction coefficient matrix and brightness calibration coefficients for each discrete band based on the band images and spectral irradiance data, and before the step of generating brightness response data based on band images acquired at different temperatures, the multispectral calibration method further includes:

The flat field correction coefficient matrix is smoothed by Gaussian filtering; the smoothed flat field correction coefficient matrix data is then normalized.

Secondly, embodiments of this application provide a multispectral calibration device for an imaging colorimeter, comprising:

The system comprises the following components: a control unit for setting up the integrating sphere light source in the calibration system and controlling it to achieve the target brightness; an adjustment unit for adjusting the detection temperature of the calibration system to reach the target temperature, which includes a reference temperature and several comparison temperatures; a first generation unit for performing band separation processing on the light source at the outlet of the integrating sphere light source through the band separation module to generate several discrete bands; an acquisition unit for acquiring band images corresponding to several discrete bands using the imaging colorimeter; a detection unit for acquiring spectral radiation data of the integrating sphere light source in different discrete bands; a first calculation unit for calculating the flat field correction coefficient matrix and brightness calibration coefficient for each discrete band based on the band images and corresponding spectral radiation data; a second generation unit for generating brightness response data based on band images acquired at different temperatures; a third generation unit for generating a temperature coefficient based on the brightness response data at the reference temperature and the comparison temperature; and a first compensation unit for compensating the brightness response of the band images based on the flat field correction coefficient matrix, the brightness calibration coefficient, and the temperature coefficient.

Optionally, the calibration system may also include a spectrophotometer;

The detection unit specifically includes:

The spectral radiation intensity distribution at the center of the integrating sphere light source outlet was detected using a spectrophotometer; the standard radiation intensity value at the center wavelength of each discrete band was detected using a spectrophotometer.

Optionally, the first computing unit specifically includes:

When the spectral radiation intensity distribution does not meet the brightness uniformity condition, adjust the operating parameters of the integrating sphere light source until the spectral radiation intensity distribution meets the brightness uniformity condition; when the spectral radiation intensity distribution meets the brightness uniformity condition, generate a flat field correction coefficient matrix based on the brightness mean of the band image and the brightness value of the pixel; generate a brightness calibration coefficient based on the brightness mean of the band image and the standard radiation intensity value corresponding to the discrete band.

Optionally, the second generation unit specifically includes:

Obtain the average brightness data of band images acquired at different temperatures; generate brightness response data based on the average brightness data, flat field correction coefficient matrix, and brightness calibration coefficient.

Optionally, the adjustment unit specifically includes:

The colorimeter generates internal temperature parameters using an internal temperature sensor and ambient temperature parameters using an ambient temperature sensor. The current detection temperature is then generated based on the colorimeter's thermal coupling factor, thermal time factor, internal temperature parameters, and ambient temperature parameters. If the detection temperature does not reach the target temperature range, the ambient temperature and/or the colorimeter's internal temperature are adjusted until the detection temperature meets the target. Once the detection temperature reaches the target temperature range, the calibration system is confirmed to have reached the target temperature.

Optionally, after the first compensation unit, the multispectral calibration device further includes:

The setting unit is used to set the automatic calibration cycle and automatic calibration change rate, and to calibrate the calibration system using the built-in standard light source; the second calculation unit is used to calculate the drift coefficient based on the currently measured brightness response data and the initially calibrated brightness response data during the calibration process; the second compensation unit is used to apply the drift coefficient to subsequent brightness response compensation.

Optionally, after the first computation unit and before the second generation unit, the multispectral calibration device further includes:

The filtering unit is used to perform Gaussian filtering smoothing on the flat field correction coefficient matrix; the normalization unit is used to normalize the smoothed flat field correction coefficient matrix data.

Thirdly, embodiments of this application provide an electronic device, including:

Processor, memory, input/output units, and bus;

The processor is connected to memory, input/output units, and a bus;

The memory stores a program, which the processor calls to execute, such as the first aspect and any optional multispectral calibration method of the first aspect.

Fourthly, embodiments of this application provide a computer-readable storage medium storing a program that, when executed on a computer, performs the first aspect and any optional multispectral calibration method of the first aspect.

As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

In this application, an integrating sphere light source is first set up in the calibration system to control the integrating sphere light source to achieve the target brightness. The calibration system includes an imaging colorimeter and a band separation module. The detection temperature of the calibration system is adjusted to reach the target temperature, which includes a reference temperature and several contrast temperatures. The band separation module performs band separation processing on the light source at the exit port of the integrating sphere light source to generate several discrete bands. The imaging colorimeter acquires band images corresponding to the discrete bands. Spectral radiation data of the integrating sphere light source in different discrete bands are obtained. Based on the band images and spectral radiation data, the flat-field correction coefficient matrix and brightness calibration coefficient of each discrete band are calculated. Brightness response data is generated based on the band images acquired at different temperatures. Temperature coefficients are generated based on the brightness response data at the reference temperature and the contrast temperatures. Brightness response compensation is performed on the band images based on the flat-field correction coefficient matrix, brightness calibration coefficients, and temperature coefficients.

By setting an integrating sphere in the calibration system and establishing different detection temperatures, and then separating the light source of the integrating sphere into different bands, different discrete bands are generated for calibration. Next, using the spectral radiation data of the integrating sphere light source in each band, two calibration data sets are generated for each band image: a flat-field correction coefficient matrix and a brightness calibration coefficient. Furthermore, corresponding brightness response data is generated based on the band image at each detection temperature. These brightness response data are then analyzed with the response data at a reference temperature to generate a temperature coefficient that can handle different detection temperatures. The temperature coefficient adjusts for differences in brightness response data. Finally, brightness response compensation is performed on the band image based on the flat-field correction coefficient matrix, brightness calibration coefficient, and temperature coefficient. This calibration method adds discrete band calibration, meeting the spectral characteristics testing requirements of new displays. Moreover, flat-field correction and brightness calibration are not separated, forming a systematic and integrated calibration method. The introduction of brightness response data analysis at different detection temperatures reduces data drift in the calibration system, improving the accuracy of optical testing of the display.

Attached Figure Description

To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

Figure 1 is a schematic diagram of the multispectral calibration method of the imaging colorimeter of this application;

Figure 2 is a schematic diagram of the method for generating spectral radiation data according to this application;

Figure 3 is a schematic diagram of the method for calculating the flat field correction coefficient matrix and the brightness calibration coefficient in this application;

Figure 4 is a schematic diagram of the method for generating luminance response data according to this application;

Figure 5 is a schematic diagram of the method for adjusting the detection temperature of the calibration system in this application;

Figure 6 is a schematic diagram of the periodic compensation method in this application;

Figure 7 is a schematic diagram of the preprocessing method for the flat field correction coefficient matrix of this application;

Figure 8 is a schematic diagram of the multispectral calibration device for the imaging colorimeter of this application;

Figure 9 is a schematic diagram of the multispectral calibration electronic device for the imaging colorimeter of this application;

Figure 10 is a schematic diagram of the structure of the calibration system of this application;

Figure 11 is a schematic diagram of the filter wheel structure of this application.

Detailed Implementation

In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and/or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and/or a collection thereof.

It should also be understood that the term “and/or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

In the existing technology, with the continuous updating of display technology, the structure of new displays is becoming more and more complex, and the arrangement of pixels is becoming more and more precise. Furthermore, with the continuous expansion of display application fields, the structure of displays is constantly changing, such as flexible screens, foldable screens, curved screens, splicing screens, AR screens, etc. More and more new displays are emerging, and different new displays have different special structures. For example, flexible screens have extension structures, foldable screens have folding areas, and splicing screens have splicing edges. These special structures are used to complete their functionality in specific fields.

As the precision of new displays gradually improves, existing calibration techniques face numerous challenges. Due to the unique structure of these displays, individual brightness and color uniformity testing of specific structures is often required. The display technology of these new displays is highly precise, especially the technology specific to their unique structures, which is unique to this type of display. This necessitates the use of different discrete spectral bands in the calibration system. However, existing calibration methods are mostly designed for specific bands or fixed light source conditions, lacking comprehensive calibration capabilities across the entire multispectral band. In other words, existing calibration methods are insufficient to meet the spectral characteristics testing requirements of new displays. Furthermore, in multispectral discrete band calibration, flat-field correction and brightness calibration are crucial data points. However, existing calibration techniques often treat flat-field correction and brightness calibration as separate processes, lacking a systematic integration method, resulting in significant differences in their calibration outcomes. Secondly, the calibration of new displays often requires the introduction of external light sources with specific discrete bands and specific manipulations of the display's unique structure to test the brightness and color uniformity of the specific structure during operation. This necessitates calibration under more complex ambient lighting conditions. Conventional calibration and testing equipment struggles to maintain stable measurement accuracy because the more conditions introduced, the more environmental factors cause drift in the calibration and testing system, leading to deviations in the calibration response data. This is particularly true for ambient temperature and the internal temperature of the colorimeter, which in turn affect the calibration results and compromise the reliability of the measurements. Furthermore, existing calibration methods are incompatible with the display technologies of new displays, reducing the accuracy of optical testing of these displays.

Based on this, this application discloses a multispectral calibration method, apparatus, electronic device and storage medium for an imaging colorimeter, which can improve the detection requirements of displays with different display technologies and spectral characteristics.

The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

The method described in this application can be applied to servers, devices, terminals, or other devices with logical processing capabilities; therefore, this application does not limit its application. For ease of description, the following description uses a terminal as the executing entity.

Please refer to Figure 1. This application provides an embodiment of a multispectral calibration method for an imaging colorimeter, including:

101. Set up an integrating sphere light source in the calibration system and control the integrating sphere light source to achieve the target brightness. The calibration system includes an imaging colorimeter and a band separation module.

In this embodiment, the terminal first sets up an integrating sphere light source in the calibration system and controls the integrating sphere light source to reach the target brightness. The calibration system includes an imaging colorimeter and a band separation module.

For example, in this embodiment, the integrating sphere light source is set to a standard light source D65 (color temperature approximately 6500K) to simulate the light-emitting characteristics of the new display screen under natural sunlight conditions. The output power of the integrating sphere light source is adjusted to 100 cd/m², which is used as the target brightness value and also the reference brightness value. The integrating sphere light source with a barium sulfate reflective coating on its inner wall serves as a uniform light source. An LED light is installed inside the integrating sphere light source as the light source, with a power of 150W and a color temperature of 6500K. The exit diameter of the integrating sphere light source is set to 200mm. An imaging colorimeter is placed at the exit and images the exit of the integrating sphere light source. The distance between the image sensor and the exit of the integrating sphere light source is 300mm. Multiple reflections inside the integrating sphere light source form uniform diffused illumination, ensuring that the light intensity received by the surface of the image sensor is uniform and consistent, with the illuminance deviation controlled within ±0.5%.

In this embodiment, the imaging colorimeter uses a high-resolution CMOS image sensor for imaging. The image sensor has a resolution of 4096x3000 pixels, a pixel size of 3.45μm×3.45μm, and a dynamic range of 60dB. The distance between the image sensor and the exit port of the integrating sphere light source is 300mm, and a precision adjustment mechanism ensures that the optical axis of the image sensor coincides with the central axis of the exit port of the integrating sphere light source. It should be noted that the parameter settings in this embodiment and other embodiments of the present invention are merely examples and are not intended to limit the present invention.

102. Adjust the detection temperature of the calibration system to reach the target temperature, which includes the reference temperature and several comparison temperatures.

The terminal adjusts the temperature of the calibration system. First, the terminal determines the temperature type that affects the sampling data in the calibration system. Then, it determines several temperature sampling values corresponding to the temperature type. Next, it calculates the corresponding detection temperature based on the several temperature sampling values and the corresponding influencing factors. By adjusting the parameters of the calibration system, the temperature sampling values change as expected, thereby enabling the entire calibration system to reach the required detection temperature.

103. The light emitted from the integrating sphere light source is processed by band separation module to generate several discrete bands.

After setting the temperature, the terminal uses the band separation module to perform band separation processing on the light emitted from the integrating sphere light source, generating several discrete bands. Specifically, please refer to Figure 10, which is a schematic diagram of the calibration system. This imaging colorimeter multispectral calibration system includes an integrating sphere light source, an imaging colorimeter, a band separation module (not shown), a PC, and a spectrophotometer. The function of the spectrophotometer will be explained later. It should be noted that the band separation module can be built into the imaging colorimeter or it can be separate from the imaging colorimeter and set up independently in the calibration system; this is not limited here.

Specifically, the band separation module can be a filter wheel. In this embodiment, an imaging colorimeter with an internal filter wheel equipped with eight narrowband filters is used to image the output port of the integrating sphere light source. Please refer to Figure 11, which is a schematic diagram of the filter wheel structure of the imaging colorimeter. The filter wheel includes several filters and supports switching. The imaging colorimeter is equipped with a high-sensitivity CMOS image sensor with a resolution of 4096x3000 pixels, a dynamic range of 12 bits, and a signal-to-noise ratio greater than 60dB. The distance between the image sensor and the output port of the integrating sphere light source is 300mm, and a precision adjustment mechanism ensures that the optical axis of the image sensor coincides with the central axis of the output port of the integrating sphere light source. The filter wheel needs to contain narrowband filters for at least the following bands:

Band 1: 380nm-430nm, center wavelength 405nm, full width at half maximum (FWHM) 20nm;

Band 2: 430nm-480nm, center wavelength 455nm, full width at half maximum (FWHM) 20nm;

Band 3: 480nm-530nm, center wavelength 505nm, full width at half maximum (FWHM) 20nm;

Band 4: 530nm-580nm, center wavelength 555nm, full width at half maximum (FWHM) 20nm;

Band 5: 580nm-630nm, center wavelength 605nm, full width at half maximum (FWHM) 20nm;

Band 6: 630nm-680nm, center wavelength 655nm, full width at half maximum (FWHM) 20nm;

Band 7: 680nm-730nm, center wavelength 705nm, full width at half maximum (FWHM) 20nm;

Band 8: 730nm-780nm, center wavelength 755nm, full width at half maximum (FWHM) 20nm.

For each band, the exposure time of the imaging colorimeter is set so that the response value of the image sensor is between 60% and 80% of its dynamic range, avoiding overexposure or underexposure. Specifically, the exposure times for bands 1 to 8 can be set to: 120ms, 100ms, 80ms, 60ms, 70ms, 90ms, 110ms, and 130ms, respectively.

104. Acquire band images corresponding to all discrete bands using an imaging colorimeter.

The terminal acquires band images corresponding to all discrete bands using an imaging colorimeter. Specifically, during acquisition, the imaging colorimeter maintains a fixed distance of 300mm from the integrating sphere light source exit port, as described above, ensuring that the integrating sphere light source exit port completely covers the field of view of the imaging colorimeter. The optical axis of the imaging colorimeter coincides with the central axis of the integrating sphere light source exit port, ensuring the central symmetry of the image. Furthermore, for each discrete band, 10 frames are continuously acquired and averaged to obtain the band image referred to in this specification, thus reducing the influence of random noise. The acquired images have a resolution of 4096x3000 pixels, a bit depth of 12 bits, and are saved in a lossless format.

105. Obtain spectral radiation data of the integrating sphere light source in different discrete bands.

The terminal acquires spectral radiation data of the integrating sphere light source in different discrete bands and uses it as a standard reference. Subsequently, images in different bands are calibrated based on the spectral radiation data. The specific method of generating spectral radiation data will be explained later.

106. Calculate the flat field correction coefficient matrix and brightness calibration coefficient for each discrete band based on the band image and corresponding spectral radiation data.

After the terminal acquires the spectral radiation data of different discrete bands, it calculates the flat field correction coefficient matrix and brightness calibration coefficient of each discrete band based on the band image and the corresponding spectral radiation data. Specifically, the calculation is performed using the pixel information on the band image. The detailed calculation steps will be explained in detail in subsequent embodiments.

107. Generate corresponding brightness response data based on band images acquired at different temperatures.

The terminal generates brightness response data based on band images collected at different temperatures. Specifically, it generates brightness response data adapted to the calibration of the new display screen based on pixel information in the band images at different temperatures. The specific generation method will be explained later. In this embodiment, for traditional displays, the brightness response data uses the brightness data from the band images.

108. Generate a temperature coefficient based on the brightness response data at the reference temperature and the brightness response data at the comparison temperature.

This embodiment requires dynamic compensation for system drift caused by environmental factors. Environmental factors such as temperature and humidity fluctuations can cause drift in the calibration measurement system, affecting calibration accuracy. Therefore, this embodiment designs a dynamic compensation mechanism as follows:

First, a temperature sensor is integrated into the imaging colorimeter to monitor its internal temperature in real time, and an ambient temperature sensor is used to monitor the ambient temperature outside the imaging colorimeter in real time. The temperature sensors have an accuracy of ±0.1℃ and a sampling frequency of 1Hz. Specifically, the ambient temperature and the colorimeter's internal temperature are the key indicators of the detection temperature described in step 102.

The terminal generates a temperature coefficient based on the brightness response data at the reference temperature and the comparison temperature, thus establishing a model relating temperature to the calibration system's response drift. For example, using 25℃ as the reference temperature, the system's response to a standard light source can be measured at three comparison temperature points: 20℃, 30℃, and 35℃, and the temperature coefficient αT can be calculated.

αT = [(RT - R25) / (T - 25)]/ R25

Where RT represents the luminance response data at temperature T, and R25 represents the luminance response data at 25℃. It should be noted that the comparison temperature can be any temperature other than the reference temperature.

109. Perform brightness response compensation on the band image based on the flat field correction coefficient matrix, brightness calibration coefficient, and temperature coefficient.

In this embodiment, the terminal first performs flat field correction and brightness calibration on the band image based on the flat field correction coefficient matrix and the brightness calibration coefficient, and then obtains the brightness of the band image and uses the temperature coefficient to compensate for the brightness response.

R_corrected = R_measured / (1 + αT·(T_current - 25))

Where R_corrected is the luminance response data after temperature compensation, R_measured is the measured luminance response data, and T_current is the detection temperature at the current detection time.

In this embodiment, firstly, an integrating sphere light source is set up in the calibration system, and the integrating sphere light source is controlled to achieve the target brightness. The calibration system includes an imaging colorimeter and a band separation module. The detection temperature of the calibration system is adjusted to reach the target temperature, which includes a reference temperature and several comparison temperatures. The band separation module performs band separation processing on the light source at the exit port of the integrating sphere light source to generate several discrete bands. The imaging colorimeter acquires band images corresponding to all of the discrete bands. The spectral radiation data of the integrating sphere light source in different discrete bands are detected. Based on the band images and spectral radiation data, the flat-field correction coefficient matrix and brightness calibration coefficient of each discrete band are calculated. Brightness response data is generated based on the band images acquired at different temperatures. A temperature coefficient is generated based on the brightness response data at the reference temperature and the comparison temperatures. Brightness response compensation is performed on the band images based on the flat-field correction coefficient matrix, the brightness calibration coefficient, and the temperature coefficient.

By setting an integrating sphere in the calibration system and establishing different detection temperatures, and then separating the light source of the integrating sphere into different bands, different discrete bands are generated for calibration. Next, using the spectral radiation data of the integrating sphere light source in each band, two calibration data sets are generated for each band image: a flat-field correction coefficient matrix and a brightness calibration coefficient. Furthermore, corresponding brightness response data is generated based on the band image at each detection temperature. These brightness response data are then analyzed with the response data at a reference temperature to generate a temperature coefficient that can handle different detection temperatures. The temperature coefficient adjusts for differences in brightness response data. Finally, brightness response compensation is performed on the band image based on the flat-field correction coefficient matrix, brightness calibration coefficient, and temperature coefficient. This calibration method adds discrete band calibration, meeting the spectral characteristics testing requirements of new displays. Moreover, flat-field correction and brightness calibration are not separated, forming a systematic and integrated calibration method. The introduction of brightness response data analysis at different detection temperatures reduces data drift in the calibration system, improving the accuracy of optical testing of the display.

Please refer to Figure 2. This application provides an embodiment of a method for generating spectral radiance data. The calibration system further includes a spectrophotometer, comprising:

201. Use a spectrophotometer to detect the spectral radiation intensity distribution at the center of the outlet of the integrating sphere light source.

202. Use a spectrophotometer to detect the standard radiation intensity value at the center wavelength of each discrete band.

In this embodiment, the terminal uses a spectrophotometer certified by the National Metrology Institute to measure the spectral radiant intensity distribution at the center of the integrating sphere light source's exit port, serving as standard reference data. This spectrophotometer has a wavelength range of 380nm-780nm, a wavelength accuracy of ±0.2nm, and a radiant intensity measurement accuracy better than ±2%. Next, the terminal uses the spectrophotometer to detect the standard radiant intensity value at the center wavelength of each discrete band, expressed in W/(sr·m²·nm).

In this embodiment, the spectral radiance distribution and the standard radiance value at the center wavelength of the discrete band are similar in data type but serve different purposes. The spectral radiance distribution is used to determine the uniformity of the integrating sphere light source, and in certain cases, it can even be combined with the band image to generate a flat-field correction coefficient matrix. The standard radiance value at the center wavelength of the discrete band is used for brightness calibration, which will be described in detail in subsequent embodiments.

Please refer to Figure 3. This application provides an embodiment of a method for calculating the flat field correction coefficient matrix and the brightness calibration coefficient, including:

301. When the spectral radiation intensity distribution does not meet the brightness uniformity condition, adjust the operating parameters of the integrating sphere light source until the spectral radiation intensity distribution reaches the brightness uniformity condition.

302. When the spectral radiation intensity distribution meets the condition of uniform brightness, generate a flat field correction coefficient matrix based on the average brightness value of the band image and the brightness value of the pixel.

303. Generate brightness calibration coefficients based on the average brightness value of the band image and the standard radiation intensity value corresponding to the discrete band.

In this embodiment, the terminal analyzes the brightness uniformity of the integrating sphere light source based on the spectral radiation intensity distribution. When the uniformity is not up to standard, it is necessary to adjust the position of the LED light source or replace it with an integrating sphere light source with a different output port so that the spectral radiation intensity distribution reaches the brightness uniformity condition.

For each band of the image, a flat-field correction coefficient matrix is calculated. Flat-field correction aims to eliminate image non-uniformity caused by the optical system, image sensor inhomogeneities, and the slight inhomogeneities of the integrating sphere light source itself. When the spectral radiance distribution meets the brightness uniformity condition, the flat-field correction coefficient matrix is generated based on the average brightness value of the band image and the brightness value of each pixel. For a conventional display screen, the average brightness value Iavg of each band image is first calculated. For each pixel (x, y) in the band image, its ratio to the average brightness value is calculated to obtain the flat-field correction coefficient matrix F(x, y), as shown in the following formula:

F(x, y) = Iavg / I(x, y)

Where I(x, y) is the brightness value of each pixel (x, y) in the band image.

For new types of displays, the flat-field correction coefficient matrix F(x, y) needs to be adjusted according to the spectral radiance intensity distribution, as shown in the following formula:

in, This is the adjusted flat field correction coefficient matrix. For integrating sphere light sources in discrete bands The detection spectral radiation distribution, For integrating sphere light sources in discrete bands Ideal spectral radiation distribution Discrete band The spectral sensitivity of pixels (x, y) on the band image is determined by introducing both measured and ideal spectral radiation distributions, combined with the discrete band values for each pixel in the band image. The spectral sensitivity can be used to analyze the response capability of each pixel of the new display to discrete bands, and generate a flat field correction coefficient matrix that is more suitable for the new display.

For each discrete band, the terminal needs to calculate the brightness calibration coefficient K, which is used to convert the image brightness value into an absolute radiant intensity value. The formula is as follows:

K = Sλ / Iavg

Where Sλ is the standard radiant intensity value at the center wavelength of the corresponding band measured by the spectrophotometer, in units of W/(sr·m²·nm), and Iavg is the average brightness value of the image in that band.

Secondly, to improve calibration accuracy, the above measurement process was repeated at different brightness levels at the integrating sphere light source exit port (e.g., 10 cd/m², 50 cd/m², 100 cd/m², 200 cd/m², 300 cd/m²) to obtain multiple sets of K values. Linear regression analysis was then used to obtain the functional relationship K(L) between the brightness calibration coefficient and the brightness of the integrating sphere light source.

K(L) = a·L + b

Where L is the luminance value of the integrating sphere light source, and a and b are regression coefficients. A corresponding luminance calibration function is established for each discrete band.

Please refer to Figure 4. This application provides an embodiment of a method for generating luminance response data, including:

401. Obtain the average brightness data of band images collected at different temperatures.

402. Generate luminance response data based on the mean luminance data, the flat field correction coefficient matrix, and the luminance calibration coefficient.

However, with the continuous upgrading and iteration of the structure of new displays, especially flexible foldable screens with micro-illuminated areas in the folding region, the detection of the folding region of flexible foldable screens is challenging. Due to the high extensibility of the folding region and the presence of microcircuit areas inside, the folding region exhibits response errors not only to temperature but also to different discrete wavelengths. Furthermore, the surface of flexible foldable screens more easily reflects ambient light or sensor light, forming stray light paths and leading to differences in brightness response. If the temperature coefficient is generated solely based on measured brightness at different temperatures and discrete wavelengths, the temperature coefficient compensation effect is poor.

In this embodiment, the terminal generates luminance response data using the flat field correction coefficient matrix and luminance calibration coefficients calculated from the band image. This luminance response data can represent band images of different discrete bands and incorporates the unique structure of the novel display screen. The formula is as follows:

Where RT represents the luminance response data of the calibration system at the detection temperature T. This is the brightness calibration coefficient. This represents the average brightness data of the band image. This is the flat field correction coefficient matrix. This refers to the nonlinear response coefficient of the new display screen. The calculation formula is as follows:

in, For the current discrete band The response intensity coefficient, Mean brightness data of the band image. This is the darkness/brightness threshold constant, used to avoid zero input. The maximum calibrated brightness of the new display screen on its specific structure was obtained based on historical data. This represents the nonlinear response constant of the novel display screen during the nonspecific structural brightness detection process. This represents the nonlinear response constant of the novel display screen during the specific structure brightness detection process.

The brightness response data obtained in this embodiment is used for subsequent temperature coefficient detection, and finally, the temperature coefficient is used to compensate for the brightness response of the actual band image. The temperature coefficient calculated in this way can well characterize the influence of different new display screens and discrete bands on the brightness response, and combines the flat field correction coefficient matrix and brightness calibration coefficient, instead of directly using the detected brightness, thus reducing response detection errors.

Please refer to Figure 5. This application provides an embodiment of a method for adjusting the detection temperature of a calibration system, including:

501. The internal temperature parameters of the colorimeter are generated by the internal temperature sensor installed inside the imaging colorimeter.

502. Ambient temperature parameters are generated using an ambient temperature sensor.

503. Generate the current detection temperature based on the thermal coupling factor, thermal time factor, internal temperature parameters of the colorimeter, and ambient temperature parameters of the imaging colorimeter.

504. When the detected temperature does not reach the target temperature range, adjust the ambient temperature of the calibration system and/or the internal temperature of the colorimeter until the detected temperature reaches the target.

505. When the detected temperature reaches the target temperature range, the calibration system is confirmed to have reached the target temperature.

In this embodiment, the terminal first detects the internal temperature parameters of the colorimeter using an internal temperature sensor, then generates ambient temperature parameters using an ambient temperature sensor. Next, the terminal generates the current detection temperature based on the thermal coupling factor, thermal time factor, internal temperature parameters, and ambient temperature parameters of the imaging colorimeter, using the following formula:

in, To calibrate the system at the current detection temperature, t represents the current system runtime. These are the internal temperature parameters of the colorimeter. For ambient temperature parameters, Thermal coupling factor (0≤ ≤1, reflecting the weight of the influence of the colorimeter's internal temperature on the operating temperature. The thermal time factor characterizes the speed at which an imaging colorimeter calibration system reaches thermal equilibrium.

The detection temperature calculated using the above method can balance the influence of the colorimeter's internal temperature and ambient temperature on the brightness response data. This allows for the determination of the detection temperature corresponding to each image captured by the display screen during the actual calibration process, based on the colorimeter's external and internal environments. This enables a better identification of the temperature coefficient to adjust the brightness response data, resulting in more accurate calibration. Furthermore, when the detection temperature does not reach the target temperature range, the terminal can adjust the ambient temperature of the entire calibration system, the colorimeter's internal temperature, or both simultaneously, until the detection temperature reaches the target. The colorimeter's internal temperature can be adjusted by changing its operating time. If the colorimeter's internal temperature is manually controlled, it can be cooled by shutting it down when the temperature becomes too high.

Please refer to Figure 6. This application provides an embodiment of a periodic compensation method, including:

601. Set the automatic calibration cycle and automatic calibration change rate, and use the built-in standard light source to calibrate the calibration system.

602. During the calibration process, the drift coefficient is calculated based on the currently measured brightness response data and the initially calibrated brightness response data.

603. Use the drift coefficient for subsequent brightness response compensation.

In this embodiment, the terminal also needs to be set with an automatic calibration cycle. Specifically, when the imaging colorimeter is working continuously, the system automatically performs calibration using the built-in standard light source every 24 hours or when the internal temperature of the colorimeter changes by more than 5°C. The built-in standard light source is an LED light source built into the colorimeter, and its spectral stability is better than ±0.5%/1000h.

During calibration, the difference between the currently measured luminance response data and the initially calibrated luminance response data is compared, and the drift coefficient β is calculated.

β = R_initial / R_current

Where R_initial is the luminance response data during initial calibration, and R_current is the luminance response data measured at the current time.

The drift coefficient β is applied to subsequent measurements:

R_final = R_measured × β

In addition, the system monitors changes in ambient humidity. When the relative humidity exceeds 70% or falls below 30%, the system issues a warning, alerting the operator to the potential impact of environmental conditions on the measurement.

Through the aforementioned dynamic compensation mechanism, the system can effectively cope with drift caused by environmental changes and maintain long-term stable measurement accuracy. Experimental verification shows that within the ambient temperature range of 20℃-35℃, the drift in system measurement accuracy is controlled within ±0.5%; within the relative humidity range of 30%-70%, the drift in system measurement accuracy is controlled within ±0.3%.

Please refer to Figure 7. This application provides an embodiment of a method for preprocessing a flat-field correction coefficient matrix, including:

701. Perform Gaussian filtering smoothing on the flat field correction coefficient matrix.

702. Normalize the smoothed flat field correction coefficient matrix data.

In this embodiment, to reduce the impact of noise, the terminal performs Gaussian filtering on F(x,y) for smoothing. The filter kernel size is 5×5, the standard deviation σ=1.0, and the terminal normalizes the smoothed correction coefficient matrix so that its mean is 1.0.

Please refer to Figure 8. This application provides an embodiment of a multispectral calibration device for an imaging colorimeter, comprising:

The control unit 801 is used to set the integrating sphere light source in the calibration system and control the integrating sphere light source to achieve the target brightness. The calibration system includes an imaging colorimeter and a band separation module.

The adjustment unit 802 is used to adjust the detection temperature of the calibration system so that the detection temperature reaches the target temperature, which includes the reference temperature and several comparison temperatures.

The adjustment unit 802 is specifically used to: generate internal temperature parameters of the colorimeter using an internal temperature sensor installed inside the imaging colorimeter; generate ambient temperature parameters using an ambient temperature sensor; and generate the current detection temperature based on the thermal coupling factor, thermal time factor, internal temperature parameters, and ambient temperature parameters of the imaging colorimeter. When the detection temperature does not reach the target temperature range, the unit adjusts the ambient temperature and/or the internal temperature of the colorimeter in the calibration system until the detection temperature reaches the target. When the detection temperature reaches the target temperature range, the unit determines that the calibration system has reached the target temperature.

The first generation unit 803 is used to perform band separation processing on the light source at the exit port of the integrating sphere light source through the band separation module to generate several discrete bands.

The acquisition unit 804 is used to acquire band images corresponding to all discrete bands using an imaging colorimeter.

The detection unit 805 is used to acquire spectral radiation data of the integrating sphere light source in different discrete bands.

Optionally, the calibration system also includes a spectrophotometer. The detection unit 805 is specifically used to: detect the spectral radiant intensity distribution at the center position of the integrating sphere light source exit port using the spectrophotometer; and to detect the standard radiant intensity value at the center wavelength of each discrete band using the spectrophotometer.

The first calculation unit 806 is used to calculate the flat field correction coefficient matrix and brightness calibration coefficient for each discrete band based on the band image and spectral radiation data.

The first calculation unit 806 is specifically used for: adjusting the operating parameters of the integrating sphere light source when the spectral radiance distribution does not meet the brightness uniformity condition, until the spectral radiance distribution reaches the brightness uniformity condition; generating a flat-field correction coefficient matrix based on the average brightness value of the band image and the brightness value of the pixels when the spectral radiance distribution meets the brightness uniformity condition; and generating brightness calibration coefficients based on the average brightness value of the band image and the standard radiance value corresponding to the discrete bands.

The filtering unit 807 is used to perform Gaussian filtering smoothing on the flat field correction coefficient matrix.

Normalization unit 808 is used to normalize the smoothed flat field correction coefficient matrix data.

The second generation unit 809 is used to generate brightness response data based on band images acquired at different temperatures.

The second generation unit 809 is specifically used to: acquire the average brightness data of band images collected at different temperatures; and generate brightness response data based on the average brightness data, the flat field correction coefficient matrix, and the brightness calibration coefficient.

The third generation unit 810 is used to generate a temperature coefficient based on the brightness response data at the reference temperature and the brightness response data at the comparison temperature.

The first compensation unit 811 is used to perform brightness response compensation on the band image based on the flat field correction coefficient matrix, brightness calibration coefficient and temperature coefficient.

In addition, this application also provides an improved embodiment of the aforementioned multispectral calibration device for imaging colorimeters regarding period compensation, the device further comprising:

Setting unit 812 is used to set the automatic calibration cycle and automatic calibration change rate, and to calibrate the calibration system using the built-in standard light source.

The second calculation unit 813 is used to calculate the drift coefficient based on the currently measured brightness response data and the initially calibrated brightness response data during the calibration process.

The second compensation unit 814 is used to apply the drift coefficient to subsequent brightness response compensation.

Please refer to Figure 9. This application provides an electronic device, including:

Processor 901, memory 902, input/output unit 903, and bus 904.

The processor 901 is connected to the memory 902, the input/output unit 903, and the bus 904.

The memory 902 stores a program, and the processor 901 calls the program to execute the multispectral calibration method shown in Figures 1, 2, 3, 4, 5, 6, and 7.

This application provides a computer-readable storage medium on which a program is stored. When the program is executed on a computer, it performs the multispectral calibration method shown in Figures 1, 2, 3, 4, 5, 6 and 7.

Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims (10)

1. A method for multispectral calibration of an imaging colorimeter, comprising:

Setting an integrating sphere light source in a calibration system, and controlling the integrating sphere light source to reach target brightness, wherein the calibration system comprises an imaging colorimeter and a wave band separation module;

The method comprises the steps of adjusting the detection temperature of the calibration system to enable the detection temperature to reach a target temperature, wherein the target temperature comprises a reference temperature and a plurality of comparison temperatures;

performing band separation processing on a light source of an emission port of the integrating sphere light source through the band separation module to generate a plurality of discrete bands;

Acquiring band images corresponding to all the plurality of discrete bands through an imaging colorimeter;

Acquiring spectral radiation data of the integrating sphere light source in different discrete wave bands;

calculating a flat field correction coefficient matrix and a brightness calibration coefficient of each discrete wave band according to the wave band image and the corresponding spectrum radiation data;

Generating corresponding brightness response data according to the wave band images acquired at different temperatures;

Generating a temperature coefficient according to the brightness response data of the reference temperature and the brightness response data of the contrast temperature;

And carrying out brightness response compensation on the band image according to the flat field correction coefficient matrix, the brightness calibration coefficient and the temperature coefficient.

2. The multi-spectral calibration method according to claim 1, wherein the calibration system further comprises a spectrophotometer;

the step of acquiring the spectral radiation data of the integrating sphere light source in different discrete wavebands comprises the following steps:

Detecting spectral radiation intensity distribution at the center of an exit port of the integrating sphere light source by using a spectrophotometer;

A spectrophotometer is used to detect the standard radiation intensity values at the center wavelength of each discrete band.

3. The method of multispectral calibration of claim 2, wherein the step of calculating a flat field correction coefficient matrix and a luminance calibration coefficient for each discrete band from the band image and the corresponding spectral radiation data comprises:

When the spectrum radiation intensity distribution does not accord with the brightness uniformity condition, the operation parameters of the integrating sphere light source are adjusted until the spectrum radiation intensity distribution reaches the brightness uniformity condition;

When the spectrum radiation intensity distribution accords with the brightness uniformity condition, generating a flat field correction coefficient matrix according to the brightness average value of the band image and the brightness value of the pixel point;

And generating a brightness calibration coefficient according to the brightness average value of the band image and the standard radiation intensity value corresponding to the discrete band.

4. A method of multispectral calibration according to claim 3, wherein the step of generating luminance response data from the band images acquired at different temperatures comprises:

acquiring brightness average value data of the band images acquired at different temperatures;

and generating brightness response data according to the brightness mean value data, the flat field correction coefficient matrix and the brightness calibration coefficient.

5. A multispectral calibration method according to any one of claims 1 to 4, wherein the step of adjusting the detected temperature of the calibration system such that the detected temperature reaches a target temperature comprises:

Generating colorimeter internal temperature parameters through a colorimeter internal temperature sensor arranged in the imaging colorimeter;

Generating an ambient temperature parameter by an ambient temperature sensor;

generating a current detection temperature according to the thermal coupling factor, the thermal time factor, the internal temperature parameter of the colorimeter and the environmental temperature parameter of the imaging colorimeter;

When the detected temperature does not reach the temperature range of the target temperature, adjusting the ambient temperature of the calibration system and/or the internal temperature of the colorimeter until the detected temperature reaches the standard;

And when the detected temperature reaches the temperature range of the target temperature, determining that the calibration system reaches the target temperature.

6. The multispectral calibration method according to any one of claims 1 to 4, wherein after the step of performing luminance response compensation on the band image according to the flat field correction coefficient matrix, the luminance calibration coefficient, and the temperature coefficient, the multispectral calibration method further comprises:

setting an automatic calibration period and an automatic calibration change rate, and calibrating the calibration system by using a built-in standard light source;

in the calibration process, calculating a drift coefficient according to the currently measured brightness response data and the initially calibrated brightness response data;

The drift coefficient is used for subsequent luminance response compensation.

7. The method according to any one of claims 1 to 4, wherein after the step of calculating a flat field correction coefficient matrix and a luminance calibration coefficient for each discrete band from band images and spectral radiation data, the step of generating luminance response data from the band images acquired at different temperatures, the method further comprises:

carrying out Gaussian filtering smoothing treatment on the flat field correction coefficient matrix;

and carrying out normalization processing on the smoothed flat field correction coefficient matrix data.

8. A multispectral calibration device of an imaging colorimeter, comprising:

The control unit is used for setting an integrating sphere light source in the calibration system and controlling the integrating sphere light source to reach target brightness, and the calibration system comprises an imaging colorimeter and a wave band separation module;

The adjusting unit is used for adjusting the detection temperature of the calibration system so that the detection temperature reaches a target temperature, and the target temperature comprises a reference temperature and a plurality of comparison temperatures;

the first generation unit is used for carrying out wave band separation processing on the light source of the light source outlet of the integrating sphere light source through the wave band separation module to generate a plurality of discrete wave bands;

the acquisition unit is used for acquiring band images corresponding to all the plurality of discrete bands through the imaging colorimeter;

the detection unit is used for acquiring spectrum radiation data of the integrating sphere light source in different discrete wave bands;

The first calculation unit is used for calculating a flat field correction coefficient matrix and a brightness calibration coefficient of each discrete wave band according to the wave band image and the corresponding spectrum radiation data;

The second generation unit is used for generating brightness response data according to the wave band images acquired at different temperatures;

a third generation unit configured to generate a temperature coefficient from the luminance response data of the reference temperature and the luminance response data of the comparative temperature;

and the first compensation unit is used for carrying out brightness response compensation on the band image according to the flat field correction coefficient matrix, the brightness calibration coefficient and the temperature coefficient.

9. The multi-spectral calibration apparatus according to claim 8, wherein the calibration system further comprises a spectrophotometer;

The detection unit further includes:

Detecting spectral radiation intensity distribution at the center of an exit port of the integrating sphere light source by using a spectrophotometer;

A spectrophotometer is used to detect the standard radiation intensity values at the center wavelength of each discrete band.

10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a program which, when executed on a computer, performs the multispectral calibration method according to any one of claims 1 to 7.