CN112288785B - Data processing method, system and storage medium for subaperture scanning flat field calibration - Google Patents

Abstract

The invention discloses a data processing method, a system and a storage medium for sub-aperture scanning flat field calibration, wherein the method comprises the following steps: s1: obtaining an image I of a sub-aperture light source passing through a telescope_i(ii) a S2: said image I_iIdentifying crosstalk information and light spot information to obtain a template A containing the crosstalk information and the light spot information; s3: registering image I according to the template A_RiPerforming spot segmentation to obtain a spot radius R_iAnd spot center O_i(ii) a S4: for all spot radii R_iAccumulating and averaging to obtain consistent light spot radius R of the image formed by the telescope sub-aperture light source; s5: taking R as the radius of the light spot, O_iDetermining a spot circle area for the spot center and calculating the I_iThe gray level mean value DN of all pixel points in the light spot circle area in the image_i. By the method, the interference of the detector crosstalk on the calibration data processing can be effectively removed, and the flat field calibration precision is effectively improved.

Description

Data processing method, system and storage medium for sub-aperture scanning flat-field calibration

technical field

The invention relates to the field of radiation calibration, in particular to a data processing method, system and storage medium for sub-aperture scanning flat-field calibration sub-aperture scanning flat-field calibration.

Background technique

In order to improve the resolution and light-gathering ability of optical telescopes, telescopes have come out one after another since the 21st century. The precise flat-field calibration of the telescope is an important part of its development and operation. The reliability of observational data and the depth and breadth of application depend to a large extent on the accuracy of the instrument's flat-field calibration.

The sub-aperture scanning-based flat-field calibration method simulates a full-aperture uniform and stable flat-field light source by scanning the sub-aperture light source according to the idea of small and big. This method can effectively improve the uncertainty caused by the traditional large-size flat screen method due to uneven luminosity and stray light. At the same time, it can effectively avoid the problems that the large-aperture integrating sphere is difficult to prepare and is not suitable for the field calibration experiment of ground-based telescopes. The scanning mechanism based on the sub-aperture scanning method is shown in Figure 1. The sub-aperture scanning mechanism can realize horizontal and vertical two-dimensional position adjustment, as well as the direction adjustment of pitch and azimuth. The sub-aperture light source is irradiated to the optical system to be measured after passing through the collimating optical system.

When the output light of the sub-aperture light source is collimated, it has many significant advantages, such as reducing the interference of stray light on the calibration of the flat-field radiation, and effectively distinguishing the imaging detector crosstalk and ghost images in the calibration image of the sub-aperture scanning , and eliminate the crosstalk to avoid the influence of detector crosstalk on the calibration results.

The calibration image data processing process based on this scheme is shown in Figure 2. This scheme obtains a full-aperture plan light source with a full field of view through the position of the sub-aperture light source, the scanning method of the field of view, and subsequent image processing. First, adjust and fix the pointing angle of the sub-aperture light source, so that the sub-aperture light source is aligned with a certain field of view of the telescope; then, according to the scanning path, the telescope is imaged respectively, and the full-aperture image under a single field of view is obtained through image processing; then the sub-aperture is adjusted. According to the pointing angle of the light source, the telescope is imaged according to the scanning path to obtain full-aperture images in different fields of view; finally, the flat-field image is obtained through image processing, and then the calibration coefficient of the optical system is solved. Aiming at the data processing of sub-aperture scanning flat-field calibration, the present invention proposes a method for quickly and effectively extracting light spots from a single sub-aperture calibration image and eliminating crosstalk.

The sub-aperture scanning method has high requirements on the data processing of the calibration image, and improper calibration data processing will introduce additional calibration uncertainty. For example, detector crosstalk, nonlinearity, optical system processing and adjustment errors, BrignterFatter effect, light source luminosity changes, exposure time, ambient temperature changes and stray light interference during the calibration process will all have an impact on the flat-field calibration accuracy. A single sub-aperture calibration image is usually a weak spot image with a weak gray level. In addition, due to the pointing error of the sub-aperture light source, there is a slight shift in the spot image at different scanning positions. The extraction of the spot image and the calculation of the brightness value of the spot image will directly affect the final calibration accuracy. In addition, how to realize the identification of crosstalk and ghost images, and how to eliminate ghost images is also an important factor affecting the final calibration accuracy. Conventional image preprocessing and target recognition and segmentation algorithms are difficult to be directly applied to the calibration algorithm based on sub-aperture scanning, and each link of the sub-aperture scanning calibration algorithm needs to be designed accordingly to improve the final calibration accuracy.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a technical solution for data processing of sub-aperture scanning flat-field calibration in view of the above-mentioned defects of the prior art, so as to solve the problem of low precision of the existing sub-aperture scanning-based calibration algorithm.

The purpose of the present invention can be achieved through the following technical measures:

A first aspect of the present application provides a data processing method for sub-aperture scanning flat-field scaling sub-aperture scanning flat-field scaling, the method comprising:

S1: obtain the image I _i of the sub-aperture light source after passing through the telescope;

S2: The image I _i is identified by crosstalk information and light spot information, and a template A that includes the crosstalk information and the light spot information is obtained; specifically: S21: The image I _i is registered to obtain a registration image I _Ri ;

S3: perform spot segmentation on the registration image I _Ri according to the template A to obtain a spot radius R _i and a spot center O _i ;

S4: Accumulate and average all the spot radii R _i to obtain the consistent spot radius R of the image formed by the telescope on the sub-aperture light source;

S5: Taking R as the spot radius and O _i as the spot center, determine the spot circle area, and calculate the gray mean value DN _i of all pixels located in the spot circle area in the I _i image.

S6: Sum up all the DN _i calculated based on the sub-aperture, and calculate the full-aperture grayscale mean DN under the current field of view according to the following formula: DN=k·∑DN _i , where k is the correction coefficient;

S7: Obtain the full-aperture grayscale mean value DN in the current field of view, and establish a mapping relationship between the DN and the radiance of the light source.

Further, step S1 includes:

S11: control the sub-aperture light source to turn on, image the telescope, and obtain a noise floor image I _noise1 about the environment and the system itself;

S12: control the sub-aperture light source to turn off, image the telescope, and obtain the image I ₀ formed by the sub- _aperture light source at the position Li;

S13: Control the sub-aperture light source to turn off, image the telescope, and obtain a noise floor image I _noise2 about the environment and the system itself;

S14: Calculate the image I _i according to the following formula:

I _i =I ₀ -(I _noise1 +I _noise2 )/2, (i=1,2,3,...,n).

Further, step S21 includes:

Taking the image I ₁ as the standard image, and taking the image I _i (i=2, 3, . . . n, n is a positive integer) as the image to be registered, the image I ₁ and the image I _i (i=2 , 3, . . . n, n is a positive integer), perform registration based on image features, and obtain a registered image set I _Ri , where I _R1 =I ₁ .

Further, step S2 includes:

S22: Taking the image I _R1 as the reference image I _r , all other images I _Ri in the image set I _Ri are compared with the reference image I _r and take the absolute value to obtain the difference image I _Di ;

S23: establish a two-dimensional matrix A1 with the same size as the _IDi , sum the corresponding pixel grayscale values of the _IDi , and fill the obtained grayscale value sum to the corresponding pixel position of the two-dimensional matrix A1;

S24: Perform binarization processing on the two-dimensional matrix A1, and perform a morphological closing operation, thereby obtaining a template A including crosstalk information and light spot information.

Further, step S3 includes:

S31: carry out logical "AND" operation to image I _Ri and template A, obtain about image I _Ri with crosstalk information and light spot information;

S32: Gradually increase the spot radius with a predetermined length step, and take the average spot gray level of the edge area as the constraint condition, and the average light spot gray level of the edge area as the target value, and find the spot radius R _i when the average light spot gray value is the largest and The center O _i of the light spot; the constraint conditions include: the average gray value of the edge area corresponding to the light spot area is within a preset range.

Further, the preset length step is 1.

Further, "calculating the gray mean value DN _i of all pixels located in the spot circle area in the I _i image" includes:

Traverse all the pixel points in the described I _i image, when the distance between a certain pixel point position and the spot center O _i is less than the spot radius R _i , then it is determined that the current pixel point is located in the described spot circle area, and all pixel points are traversed After completion, calculate the grayscale mean value DN _i of all the pixel points located in the light spot circle area in the I _i image.

Further, the method includes:

A corresponding relationship between the grayscale mean value DN _i and the radiance of the light source is established.

A second aspect of the present application provides a computer storage medium, where a computer program is stored in the computer storage medium, and when the computer program is executed by a processor, the method steps described in the first aspect of the present application are implemented.

A third aspect of the present application provides a sub-aperture scanning plan-field scaling sub-aperture scanning plan-field scaling data processing system, the system comprising a memory, a processor, and a data processing system stored on the memory and on the processor The running computer program is characterized in that, when the processor executes the computer program, the steps of the method according to the first aspect of the present application are implemented.

Different from the prior art, the present invention provides a data processing method, system and storage medium for sub-aperture scanning flat-field calibration. The method includes: S1: acquiring the image I _i of the sub-aperture light source after the telescope; S2: all the Described image I _i carries out crosstalk information and light spot information identification, obtains the template A that comprises described crosstalk information and light spot information; Concretely includes: S21: carry out registration to described image I _i , obtain registration image I _Ri ; S3: according to The template A performs spot segmentation on the registration image I _Ri to obtain the spot radius R _i and the spot center O _i ; S4: Accumulate and average all the spot radii R _i to obtain a consistent telescope for the sub-aperture light source. The spot radius R of the image; S5: take R as the spot radius, O _i as the spot center, determine the spot circle area, and calculate the gray mean value DN _i of all the pixels located in the spot circle area in the I _i image ; S6: sum up all DN _i calculated based on the sub-aperture, and calculate the full-aperture grayscale mean value DN under the current field of view according to the following formula: DN=k·∑DN _i , where k is the correction coefficient; S7: obtain The full-aperture grayscale mean DN in the current field of view is established, and the mapping relationship between the DN and the radiance of the light source is established.

The above method is simple and efficient in the data processing process when solving the imaging data of the full-aperture light source, and can effectively retain the gray value information of the original image; at the same time, it ensures that the images obtained by the same sub-aperture light source at different scanning positions have a consistent spot area, which can effectively remove the spot. Interference caused by inconsistent areas; crosstalk and ghost images can be identified, eliminating the influence of image detector crosstalk on calibration results.

Description of drawings

1 is a schematic diagram of a scanning mechanism for sub-aperture scanning flat-field calibration sub-aperture scanning flat-field calibration related to the prior art;

2 is a schematic flow chart of the principle of sub-aperture scanning flat-field scaling sub-aperture scanning flat-field scaling related to the prior art;

3 is a flowchart of a data processing method for sub-aperture scanning flat-field calibration sub-aperture scanning flat-field calibration related to the present invention;

Fig. 4 is the flow chart of the data processing method of another sub-aperture scanning flat-field calibration sub-aperture scanning flat-field calibration that the present invention relates to;

Fig. 5 is the flow chart of the data processing method of another sub-aperture scanning flat-field calibration sub-aperture scanning flat-field calibration that the present invention relates to;

FIG. 6 is a flowchart of another sub-aperture scanning flat-field calibration data processing method for sub-aperture scanning flat-field calibration according to the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

In order to make the description of the present disclosure more detailed and complete, the following provides an illustrative description of the embodiments and specific embodiments of the present invention; but this is not the only form of implementing or using the specific embodiments of the present invention. The features of various specific embodiments as well as method steps and sequences for constructing and operating these specific embodiments are encompassed in the detailed description. However, other embodiments may also be utilized to achieve the same or equivalent function and sequence of steps.

Please refer to FIG. 3 , which is a flowchart of a data processing method for sub-aperture scanning flat-field calibration according to the present invention. The method includes:

S1: obtain the image I _i of the sub-aperture light source after passing through the telescope;

S2: The image I _i is identified by crosstalk information and light spot information, and a template A that includes the crosstalk information and the light spot information is obtained; specifically: S21: The image I _i is registered to obtain a registration image I _Ri ;

S3: perform spot segmentation on the registration image I _Ri according to the template A to obtain a spot radius R _i and a spot center O _i ;

S4: Accumulate and average all the spot radii R _i to obtain the consistent spot radius R of the image formed by the telescope on the sub-aperture light source;

S5: take R as the spot radius, O _i as the spot center, determine the spot circle area, and calculate the gray mean value DN _i of all the pixels located in the spot circle area in the I _i image;

S6: Sum up all the DN _i calculated based on the sub-aperture, and calculate the full-aperture grayscale mean DN under the current field of view according to the following formula: DN=k·∑DN _i , where k is the correction coefficient;

S7: Obtain the full-aperture grayscale mean value DN in the current field of view, and establish a mapping relationship between the DN and the radiance of the light source.

In step S7, establishing the mapping relationship between the DN and the radiance of the light source can be specifically expressed by the following formula: DN _j =R _j ·L _j , where j is the number of sampling fields of view, and R _j is the flat-field scaling coefficient . The flat-field calibration process is completed by establishing a physical mapping relationship between the acquired gray mean value DN in a certain field of view and the actual light source radiance calibrated with a calibrated light source that can be traced to the primary standard.

The invention relates to a data processing method for sub-aperture scanning flat-field radiation calibration, which is applied to the data processing of sub-aperture scanning-based flat-field calibration data. The sub-aperture light source is white (or fixed spectral component) collimated light, and the integrating sphere light source emits a collimated light beam through the reticle and the collimating optical system, and illuminates the entrance pupil of the telescope optical system.

When designing the sub-aperture light source, the sub-aperture light source area SA, the number of scanning position points n, and the full-aperture light source area SB to be simulated must satisfy the following relationship:

S _B =n×S _A

The sub-aperture light source realizes horizontal and vertical position scanning through two-dimensional scanning mechanism, and realizes scanning field of view adjustment through pitch and azimuth adjustment.

The first aspect of the present invention provides a flat-field radiation calibration data processing method for sub-aperture scanning, which is mainly a method for quickly and effectively extracting light spots from a single sub-aperture calibration image and eliminating crosstalk. The method has high robustness, The influence of the data processing link on the calibration accuracy can be effectively reduced. The calibration data processing process based on sub-aperture scanning is shown in Figure 3. Specifically, it includes five steps: sub-aperture light source denoising, crosstalk information and ghost image information (ie spot information) identification, spot image segmentation, spot radius consistency adjustment, and spot gray mean solution. The above scheme realizes crosstalk and ghost image discrimination by means of data processing, and realizes light spot image segmentation combined with crosstalk shape and gray value characteristics. At the same time, it ensures that all sub-aperture light source calibration images have the same spot size. The calibration method is accurate and efficient, and has wide applicability in the field of flat-field radiation calibration based on subaperture scanning.

In some embodiments, as shown in FIG. 4 , step S1 includes:

S11: control the sub-aperture light source to turn on, image the telescope, and obtain a noise floor image I _noise1 about the environment and the system itself;

S12: control the sub-aperture light source to turn off, image the telescope, and obtain the image I ₀ formed by the sub- _aperture light source at the position Li;

S13: Control the sub-aperture light source to turn off, image the telescope, and obtain a noise floor image I _noise2 about the environment and the system itself;

S14: Calculate the image I _i according to the following formula:

I _i =I ₀ -(I _noise1 +I _noise2 )/2, (i=1,2,3,...,n).

Preferably, the telescope is a large aperture telescope.

In this way, by recording the noise floor images of the environment and the system itself before and after the telescope imaging, and removing the noise floor of the imaging image after the telescope imaging, the imaging image I _i can effectively exclude the environment, the system itself, and other other interference of factors.

Since the sub-aperture imaging spot I _i of all paths remains substantially unchanged at the imaging position of the detector (the scanning field of view does not change). Therefore, the crosstalk in I _i does not change with the scanning position, while the ghost image changes with the scanning position (the optical path of the light is different). Based on the above imaging position differences of crosstalk and ghost images, the specific process is shown in Figure 5.

As shown in FIG. 5, in some embodiments, step S21 includes:

Taking the image I ₁ as the standard image, and taking the image I _i (i=2, 3, . . . n, n is a positive integer) as the image to be registered, the image I ₁ and the image I _i (i=2 , 3, . . . n, n is a positive integer), perform registration based on image features, and obtain a registered image set I _Ri , where I _R1 =I ₁ .

The image registration process in step S21 is configured by selecting a registration algorithm based on image features, and the image features include image edges, contours, statistical features (eg, center of gravity) and the like.

Preferably, step S2 includes:

S22: Taking the image I _R1 as the reference image I _r , all other images I _Ri in the image set I _Ri are compared with the reference image I _r and take the absolute value to obtain the difference image I _Di ;

S23: establish a two-dimensional matrix A1 with the same size as the _IDi , sum the corresponding pixel grayscale values of the _IDi , and fill the obtained grayscale value sum to the corresponding pixel position of the two-dimensional matrix A1;

S24: Perform binarization processing on the two-dimensional matrix A1, and perform a morphological closing operation, thereby obtaining a template A including crosstalk information and light spot information.

For the threshold setting of the binarization process of the two-dimensional matrix A, the initial threshold is first calculated based on the maximum inter-class variance method, and then targeted and finely adjusted according to the characteristics of the crosstalk and circular spot actually observed.

As shown in Figure 6, step S3 includes:

S31: carry out logical "AND" operation to image I _Ri and template A, obtain about image I _Ri with crosstalk information and light spot information;

S32: Gradually increase the spot radius with a predetermined length step, and take the average spot gray level of the edge area as the constraint condition, and the average light spot gray level of the edge area as the target value, and find the spot radius R _i when the average light spot gray value is the largest and The center O _i of the light spot; the constraint conditions include: the average gray value of the edge area corresponding to the light spot area is within a preset range. Preferably, the preset length step is 1.

The constraint condition of the light spot gray value in the edge area is 0.6 to 0.7 of the central brightness, and the setting principle is determined according to the characteristics of the optical system and the sub-aperture light source device. Preferably, the edge region adopts an annular region with a radius of R and a radius of 0.95R.

In some embodiments, "calculating the grayscale mean value DN _i of all pixels located in the spot circle area in the I _i image" includes:

Traverse all the pixel points in the described I _i image, when the distance between a certain pixel point position and the spot center O _i is less than the spot radius R _i , then it is determined that the current pixel point is located in the described spot circle area, and all pixel points are traversed After completion, calculate the grayscale mean value DN _i of all the pixel points located in the light spot circle area in the I _i image.

Preferably, the method includes: establishing a corresponding relationship between the grayscale mean value DN _i and the radiance of the light source.

DN _i is the pixel gray value of the sub-aperture light source at different scanning positions in the field of view, so as to establish a corresponding relationship with the radiance of the light source. The processing process of other fields of view is the same as the above method, and finally the relationship between the light source and the pixel gray value under the full aperture of the full field of view is obtained based on the field of view interpolation or other methods.

A second aspect of the present invention provides a computer storage medium, where a computer program is stored in the computer storage medium, and when the computer program is executed by a processor, the method steps described in the first aspect of the present application are implemented.

The storage medium is a memory, and the memory may be a non-volatile storage medium, which may include but not limited to a read-only memory (Read-Only Memory, ROM), a programmable read-only memory (Programmable ROM, PROM) exemplarily. , Erasable Programmable Read-Only Memory (Erasable PROM, EPROM), Electrically Erasable Programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory (Electrically EPROM, EEPROM) or Flash Memory (Flash Memory), for example, can be any of the following: Embedded Multimedia Card (Embedded Multi Media Card, EMMC), Nor Flash, Nand Flash, etc.

Exemplarily, the memory may further include a buffer device for buffering data, such as a signal queue. The cache device may be a volatile storage medium, and may exemplarily include but not be limited to random access memory (Random Access Memory, RAM), static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM) ), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDR SDRAM), DDR2, DDR3, enhanced synchronous dynamic random access memory (Enhanced SDRAM) , ESDRAM), synchronous connection dynamic random access memory (Synchlink DRAM, SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DRAM) and so on.

A third aspect of the present invention provides a data processing system for sub-aperture scanning flat-field calibration, the system comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that , the processor implements the steps of the method described in the first aspect of the present application when the processor executes the computer program.

Illustratively, the memory may include, for example, a memory card for a smartphone, a storage component for a tablet computer, a hard disk for a personal computer, read only memory (ROM), erasable programmable read only memory (EPROM), portable compact disk read only Memory (CD-ROM), USB memory, or any combination of the above storage media. A computer-readable storage medium can be any combination of one or more computer-readable storage media.

Exemplarily, the processor may be a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or a data processing Other forms of processing unit capable of and/or instruction execution capability, and may control other components in the system to perform the desired functions. For example, a processor may include one or more embedded processors, processor cores, microprocessors, logic circuits, hardware Finite State Machine (FSM), Digital Signal Processing (DSP), or their The combination.

The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention shall be included in the protection of the present invention. within the range.

Claims (8)

1. A data processing method for flat-field calibration of sub-aperture scanning, the method comprising:

s1: obtaining an image I of a sub-aperture light source passing through a telescope_i；

S2: for the image I_iCarrying out registration to obtain a registration image I_Ri(ii) a For the image I_iIdentifying crosstalk information and light spot information to obtain a template A containing the crosstalk information and the light spot information;

s3: registering image I according to the template A_RiPerforming spot segmentation to obtain a spot radius R_iAnd spot center O_i(ii) a Step S3 includes:

s31: for image I_RiAnd performing logical AND operation on the template A to obtain an image I with crosstalk information and light spot information_Ri；

S32: gradually increasing the radius of the light spot by a preset length step, taking the mean value of the gray scale of the light spot in the edge area as a constraint condition, taking the mean value of the gray scale of the light spot in the edge area as a target value, and solving the radius R of the light spot when the mean value of the gray scale of the light spot is maximum_iAnd a spot center O_i(ii) a The constraint conditions include: the gray average value of the edge area corresponding to the light spot area is within a preset range;

s4: for all spot radii R_iAccumulating and averaging to obtain consistent light spot radius R of the image formed by the telescope sub-aperture light source;

s5: taking R as the radius of the light spot, O_iDetermining a spot circle region for the spot center and calculating the image I_iThe mean value DN of the gray levels of all the pixel points in the light spot circle area_i；

S6: for all DN calculated based on sub-aperture_iSumming, and calculating the full aperture gray scale mean value DN under the current field of view according to the following formula: DN ═ k ∑ DN_iWherein k is a correction coefficient;

s7: and acquiring a full-aperture gray mean value DN in the current field, and establishing a mapping relation between the DN and the radiation brightness of the light source.

2. The data processing method of sub-aperture scanning flat-field scaling according to claim 1, wherein the step S1 includes:

s11: control the opening of the sub-aperture light source to form a telescopeImage acquisition of a background noise image I about the environment, the system itself_noise1；

S12: controlling the sub-aperture light source to be closed, imaging the telescope and acquiring the sub-aperture light source at L_iImages formed at locations I₀；

S13: controlling the sub-aperture light source to be closed, imaging the telescope, and acquiring a background noise image I about the environment and the system_noise2；

S14: calculating to obtain an image I according to the following formula_i：

I_i＝I₀-(I_noise1+I_noise2) And/2, wherein i is 1,2,3, …, n.

3. The data processing method for sub-aperture scanning flat-field scaling according to claim 1, wherein "for said image I_iCarrying out registration to obtain a registration image I_Ri"comprises:

s21: with image I₁As a standard image, take image I_iAs the image to be registered, for the image I₁And image to be registered I_iRegistering based on image characteristics to obtain a registered image set I_RiWherein the image I to be registered_iI is 2,3, … n, n is a positive integer, I_R1＝I₁。

4. The data processing method of sub-aperture scanning flat-field scaling according to claim 1 or 3, characterized in that "for said image I" the image I is scaled_iIdentifying crosstalk information and light spot information to obtain a template A' containing the crosstalk information and the light spot information comprises the following steps:

s22: with image I_R1For reference picture I_rFor image set I_RiAll other images I in_RiAre all related to the reference image I_rTaking the difference and taking the absolute value to obtain a difference image I_Di；

S23: set up and said I_DiTwo-dimensional matrices A1 of the same size for said I_DiThe corresponding pixel gray values are summed and the sum of the obtained gray values is filled to twoDimension matrix A1 corresponds to pixel locations;

s24: and (4) performing binarization processing on the two-dimensional matrix A1, and performing morphological closed operation to obtain a template A containing crosstalk information and light spot information.

5. The data processing method for sub-aperture scanning flat-field scaling according to claim 1, wherein said predetermined length step is 1.

6. The data processing method for sub-aperture scanning flat-field scaling according to claim 1, wherein "calculating said image I_iMean value DN of gray levels of all pixels in the light spot circle area_i"comprises:

traverse the image I_iWhen the position of a certain pixel point is in the center of the light spot O_iIs less than the spot radius R_iThen judging that the current pixel point is located in the light spot circle region, and calculating the image I after all pixel points are traversed_iThe mean value DN of the gray levels of all the pixel points in the light spot circle area_i。

7. A computer storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 6.

8. A data processing system for subaperture scanning flat-field scaling, the system comprising a memory, a processor, and a computer program stored on the memory and executed on the processor, the processor when executing the computer program implementing the method of any of claims 1 to 6.

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