JP2002344978A - Image processing device - Google Patents

Abstract

(57) [Problem] To provide an image processing device capable of detecting the amount of chromatic aberration of image data captured by an imaging device and correcting the amount. The present invention relates to an original image memory, an original image readout unit, a coordinate conversion unit for performing two-dimensional coordinate conversion of original image data, and a result image for storing image data after chromatic aberration correction. The memory 4, a video writing unit 5 that controls storing image data in the result video memory 4, a result video reading unit 6, and a comparison between the image data in the original image memory 1 and the image data in the result video memory 4. A comparison unit 7 for detecting a difference between the two data, an integration counter 8 for cumulatively adding the difference, and a controller 9 are provided. A pixel value difference between a plurality of color components constituting the image data captured by the imaging device is detected, and coordinate conversion of some color components is performed so that the cumulative sum of the differences is minimized. Chromatic aberration of the image data can be accurately corrected.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a CCD (Charge Co.)
The present invention relates to an image processing apparatus that detects a chromatic aberration amount of image data captured by an imaging device such as an upled device and corrects the amount.

[0002]

2. Description of the Related Art Recently, CCDs and MOS sensors having a large number of pixels exceeding 2 million pixels have become inexpensive and photographic image quality printers have become available at low cost. Widespread. A digital camera has a feature that it does not require a film or a development process and can easily print without using expensive equipment.

[0003] In addition, many photo retouching software for performing various image processing on photographed image data are on the market, and individuals can easily carry out work of synthesizing photographs with New Year's cards and posters.

[0004]

As the number of users of digital cameras has rapidly increased, there has been an increasing demand for improved image quality of digital cameras. A digital camera forms an image of light condensed by an optical lens on an imaging surface of an imaging device. However, chromatic aberration appears due to the configuration of the lens, the focus adjustment state, the aperture of the lens, the characteristics of the imaging device, and the like.

[0005] Many recent digital cameras are equipped with a zoom lens. However, when the zoom position is changed, the configuration of the lens in the zoom lens changes, so the appearance of chromatic aberration also changes.

Chromatic aberration appears because the refractive index of light differs depending on the wavelength. For example, even if focus adjustment is performed so that a green component forms an image on an image pickup surface, if there is chromatic aberration, a red component and a blue component Is blurred on the imaging surface.

As a method of eliminating chromatic aberration, a method of performing optical correction processing or software correction processing in consideration of the configuration of the lens and the characteristics of the imaging apparatus is conceivable.
However, if these methods are adopted, there is a problem that every time the configuration of the lens is changed or the type of the imaging device is changed, the correction process must be restarted from the beginning, and the correction process is troublesome.

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and has as its object to provide an image processing apparatus capable of detecting the amount of chromatic aberration of image data picked up by an image pickup apparatus and correcting the amount. Is to do.

[0009]

In order to solve the above-mentioned problems, the present invention relates to an image processing apparatus for processing image data consisting of a plurality of color components output from an image pickup apparatus. Chromatic aberration detecting means for detecting the amount of chromatic aberration between a plurality of color components based on the image data output from the storage device, and storage after correction for storing the image data after the correction of the chromatic aberration based on the detected amount of chromatic aberration Means,
Is provided.

According to the present invention, the amount of chromatic aberration is detected and corrected on the basis of the photographed image data. Therefore, the chromatic aberration can be corrected by a relatively simple process without taking the configuration of the lens and the characteristics of the image pickup apparatus into consideration. Can be performed.

[0011]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an image processing apparatus according to the present invention will be specifically described with reference to the drawings.

FIG. 1 is a block diagram showing a schematic configuration of an embodiment of an image processing apparatus according to the present invention. The image processing apparatus shown in FIG. 1 includes an original image memory 1 for storing original image data captured by an imaging device such as a CCD or a MOS sensor, and an original image read unit 2 for controlling reading of original image data from the original image memory 1. A coordinate conversion unit (coordinate conversion means) 3 for performing coordinate conversion of two-dimensional coordinates of original image data; a result video memory (corrected storage means) 4 for storing image data after chromatic aberration correction; Video writing unit (writing control means) 5 for controlling image data to be stored in the memory
And a result video reading unit 6 that controls reading of image data from the result video memory 4, and compares the image data stored in the original image memory 1 with the image data stored in the result video memory 4. A comparison unit (difference calculation unit) 7 for detecting a difference between data, an integration counter (accumulation addition unit) 8 for accumulating the difference detected by the comparison unit 7, and a controller (chromatic aberration detection unit) 9 for controlling the whole. Have.

The image processing apparatus shown in FIG. 1 may be constituted by hardware or software. FIG.
The image processing apparatus may be built in a digital camera, provided in the form of software executable on a computer, or provided as a peripheral device of a computer.

FIG. 2 is a flowchart showing the processing operation of the image processing apparatus of FIG. Hereinafter, the processing operation of the image processing apparatus of FIG. 1 will be described based on this flowchart. When starting this flowchart, the original image memory 1 of FIG. 1 stores image data captured by the imaging device. In the following, a case where image data of R (red) component, G (green) component and B (blue) component are stored in the original image memory 1 will be described as an example.
For example, when image data of CMY (cyan, magenta, yellow) components is stored in the original image memory 1, processing can be performed in the same procedure.

First, the G component image data in the original image memory 1 is copied to the result image memory 4 (step S).
1). More specifically, the processing in step S1 is performed according to the flowchart in FIG.

First, the original image reading channel is set to the G component,
The result writing channel is set to the G component, the result reading channel is set to NONE (none), and the coordinate conversion parameters are set to no conversion.
Each is set (step S11).

Next, the pixel coordinates that have not been copied are substituted for the variable coordinates (X, Y) (step S12). Next, the pixel value of the variable coordinates (X, Y) is read from the original image memory 1 and copied to the result image memory 4 (step S13). Here, the pixel value is a value representing the gradation of the target color component.

Next, it is determined whether or not the pixel values of all coordinates have been copied from the original image memory 1 to the result image memory 4 (step S14). When the pixel values of all coordinates are repeatedly copied to the result video memory 4, the process of step S2 in FIG. 2 is performed.

In step S2, the chromatic aberration of the R component is detected according to the flowchart of FIG. First, the original image read channel is set to the R component, and the result write channel is set to NONE.
(None), the result read channel is set to the G component (step S21). Next, the initial value of the minimum cumulative difference between the pixel values of the R component and the G component is set to infinity (step S22).

Next, a predetermined parameter candidate is substituted for the coordinate conversion parameter a (step S23, parameter changing means). Next, the measured value of the integration counter 8 is reset (step S24). Next, pixel coordinates that have not yet been investigated in the investigation area for which the amount of chromatic aberration is to be detected are substituted into variable coordinates (X, Y) (step S25).

Here, as shown by a hatched portion 11 in FIG. 5, one or a plurality of investigation regions are set in regions deviated from the center of the optical axis of the imaging device. In the present embodiment, in order to simplify the processing, the chromatic aberration amount of the image data partially including the investigation region is determined based on the chromatic aberration amount detected in the investigation region. If the size of the image data is small,
When processing with a CPU that has a high-speed calculation function,
The chromatic aberration amount may be detected for the entire image data without setting the investigation area.

For different image data, an investigation area is individually set for each image data to determine the amount of chromatic aberration.

Next, using the coordinate conversion parameter a, R
The coordinate conversion of the component is performed (step S26, new coordinate calculation means). Here, the coordinates before the conversion are (X, Y), and the coordinates after the conversion are (X ′, Y ′) = f (X, Y). f () is a conversion function including a coordinate conversion parameter, and is more specifically expressed by, for example, the following equations (1) and (2).
In the expression, (X0, Y0) represents the optical axis center (the center of the image data).

[0024]

(Equation 1)

(Equation 2) In step S26, coordinate conversion of the R component is performed based on, for example, equations (1) and (2). Next, the pixel value of the coordinates (X ′, Y ′) after the coordinate conversion is calculated (step S).
27, pixel value calculation means). Here, by performing an interpolation process, the pixel value of the transformed coordinates (X ′, Y ′) is determined based on the pixel values around the transformed coordinates (X ′, Y ′).

As a specific method of the interpolation processing, for example, a linear interpolation method (bilinear method) is employed. In linear interpolation,
The four coordinates ([X], [Y]), ([X] +1, [Y]), ([X], [Y]) around the coordinates (X, Y) shown in FIG. +
1), pixel values P00, P10, P0 of ([X] +1, [Y] +1)
The pixel value of the coordinates (X, Y) is obtained based on the following equation (3) based on P1 and P11.

Pixel value of coordinates (X, Y) = (X− [X]) · (Y− [Y]) · P11 + ([X] + 1−X) · (Y− [Y]) · P01 + (X- [X]) · ([Y] + 1-Y) · P10 + ([X] + 1-X) · ([Y] + 1-Y) · P00 (3) , The pixel value P11 of FIG.
The pixel value P01 is the area of the area, the pixel value P00 is the area of the area, and the pixel value P10 is the area of the area.

By such interpolation, a pixel value can be obtained for an arbitrary coordinate position. Note that the linear interpolation method is an example of the interpolation processing, and a specific method of the interpolation processing is not particularly limited.

When the pixel value at the coordinate position after the coordinate conversion is obtained, the difference is detected by comparing both the G component and the R component pixel values (step S28). Next, step S
The difference detected at 28 is cumulatively added by the integration counter 8 (step S29).

Next, it is determined whether or not difference detection has been performed for all pixels in the investigation area (step S30). If there is any pixel for which difference detection has not been performed, step S30 is performed.
Repeat the processing after 25.

When the difference detection processing for all pixels is completed, it is next determined whether or not the value measured by the integration counter 8 is smaller than the minimum value of the accumulated difference (step S31). If it is smaller, the current measured value of the integration counter 8 is set to the minimum value of the accumulated difference, and the coordinate conversion parameter at the current time is set to the R component coordinate conversion parameter (step S32).

If it is determined in step S31 that it is not small, or if the processing in step S32 is completed,
It is determined whether or not the processing from step S23 has been performed on all the parameter candidates (step S33). If there is a parameter candidate that has not been processed yet, this candidate is set as a coordinate conversion parameter and the processing from step S23 is performed. repeat. When the processing for all parameter candidates is completed, the coordinate conversion parameters set in step S32 at that time are used as the final R-component coordinate conversion parameters, and the processing in step S3 in FIG. 2 is performed.

In step S3, the chromatic aberration of the B component is detected in accordance with the flowchart of FIG. Since the processing procedure of the flowchart of FIG. 7 is similar to that of the flowchart of FIG. 4, detailed description will be omitted. By executing the processing in step S3, the coordinate conversion parameter a for the B component is obtained.

Next, the pixel value of the R component stored in the original image memory 1 is transferred to the result image memory 4 using the coordinate transformation parameter a obtained in step S2 (step S4 in FIG. 2). FIG. 8 is a flowchart showing a detailed processing procedure of step S4. First, the original image read channel is set to the R component, the result write channel is set to the R component, and the result read channel is set to NONE (step S61).

Next, the pixel coordinates that have not been transferred are substituted into the variable coordinates (X, Y) (step S62). Next, using the coordinate transformation parameter a obtained in step S2, the transformation coordinates (X ′, X ′) corresponding to the variable coordinates (X, Y)
Y ′) = f (X, Y) is calculated (step S63). Here, f () is a conversion function including a coordinate conversion parameter, and is expressed by, for example, the above-described equations (1) and (2).

Next, a pixel value of the transformed coordinates (X ', Y') is calculated by performing an interpolation process (step S).
64). Here, the transformed coordinates (X ′, Y ′) calculated in step S63 are not necessarily integer coordinates, and there is a high possibility that the pixel value corresponding to these coordinates is not stored in the original image memory 1. Therefore, by performing an interpolation process such as the linear interpolation method described above, the transformed coordinates (X ′,
The pixel value of the transformation coordinates (X ′, Y ′) is determined based on the pixel values around Y ′).

Next, the calculated pixel value of the transformed coordinates (X ', Y') is transferred to the coordinates (X, Y) of the result video memory 4 (step S65). When the processing in step S65 is completed, it is determined whether or not all the pixel values of the R component stored in the original image memory 1 have been transferred to the result image memory 4 (step S66). If
The processing after step S62 is repeated.

When the transfer of all the pixel values of the R component is completed, the coordinate conversion parameter a calculated in step S3 is obtained.
Is used to transfer the pixel value of the B component stored in the original image memory 1 to the result image memory 4 (step S5 in FIG. 2).

FIG. 9 is a flowchart showing a detailed processing procedure of step S5. The processing procedure of the flowchart of FIG. 9 is the same as that of FIG. 8, and the pixel values stored in the original image memory 1 are read out based on the coordinates converted and transferred to the result image memory 4.

As described above, in the present embodiment, a difference in pixel value between a plurality of color components constituting image data picked up by an image pickup device such as a CCD is detected, and the cumulative addition value of the difference is minimized. To perform coordinate conversion of some color components,
Chromatic aberration of captured image data can be accurately corrected.

Normal correction of chromatic aberration is performed in consideration of the configuration of the lens, the aperture, the focus adjustment information, the characteristics of the image pickup apparatus, and the like. On the other hand, in the present embodiment, the chromatic aberration can be corrected by relatively simple processing as long as there is imaged image data, so that the chromatic aberration can be easily corrected regardless of the type of the lens or the imaging device. There is. Therefore, regardless of the image data taken by any digital camera,
The chromatic aberration can be corrected with high accuracy by a home computer.

In the above-described embodiment, an example has been described in which the coordinate conversion of the R component and the B component is performed based on the G (green) component, but the reference color component may be other than the G component. Further, when the color components are composed of components other than the RBG components, for example, CMY components, the same processing as in FIG. 2 may be performed based on one of the color components.

[0042]

As described above in detail, according to the present invention, since the amount of chromatic aberration is detected and corrected based on the image data which has been photographed, it is affected by the structure of the lens and the characteristics of the image pickup apparatus. Chromatic aberration can be corrected without any problem. Therefore, a high quality captured image that is not affected by chromatic aberration can be obtained regardless of image data captured by any digital camera.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a schematic configuration of an embodiment of an image processing apparatus according to the present invention.

FIG. 2 is a flowchart illustrating a processing operation of the image processing apparatus of FIG. 1;

FIG. 3 is a detailed flowchart of step S1 in FIG. 2;

FIG. 4 is a detailed flowchart of step S2 in FIG. 2;

FIG. 5 is a diagram illustrating a survey area.

FIG. 6 is a diagram illustrating a linear interpolation method.

FIG. 7 is a detailed flowchart of step S3 in FIG. 2;

FIG. 8 is a detailed flowchart of step S4 in FIG. 2;

FIG. 9 is a detailed flowchart of step S5 in FIG. 2;

[Explanation of symbols]

 REFERENCE SIGNS LIST 1 original image memory 2 original image readout unit 3 coordinate conversion unit 4 result image memory 5 image writing unit 6 result image readout unit 7 comparison unit 8 integration counter 9 controller

Continued on the front page F-term (reference) PP32 PP33 PP37 PP39 PQ17 PQ20 PQ22 TT09 5C079 HB01 HB02 HB11 JA23 LA24 LB01 MA02 NA03

Claims (5)

[Claims] An image processing apparatus for processing image data composed of a plurality of color components output from an imaging device, wherein the chromatic aberration between the plurality of color components is determined based on the image data output from the imaging device. An image processing apparatus comprising: a chromatic aberration detecting unit that detects an amount; and a corrected storage unit that stores image data after performing chromatic aberration correction based on the detected chromatic aberration amount. 2. The method according to claim 1, wherein the chromatic aberration detecting unit minimizes a difference between a pixel value of a specific reference color component included in the image data output from the imaging device and a pixel value of a color component other than the reference color. Coordinate conversion means for performing coordinate conversion of pixel coordinates of color components other than the reference color, and for the specific reference color component, the pixel value of each reference coordinate without performing the coordinate conversion, and the corrected storage means Stored in
2. The image according to claim 1, further comprising: a writing control unit that stores, in the corrected storage unit, a pixel value of a coordinate converted by the coordinate conversion unit for a color component other than the reference color. 3. Processing equipment. 3. The image processing apparatus according to claim 1, wherein the coordinate conversion unit is configured to minimize the difference in a part of the image data output from the imaging device that deviates from the optical axis center position of the imaging device. The image processing device according to claim 2, wherein the image processing device performs coordinate conversion. 4. A new coordinate calculating means for performing a coordinate conversion of pixel coordinates of a color component other than the reference color based on a coordinate conversion parameter whose value can be varied, and a color other than the reference color. Pixel value calculation means for calculating a pixel value of the pixel coordinate calculated by the new coordinate calculation means for each of the components; and for each of the reference coordinates, the pixel value of the reference color component and the pixel value other than the reference color component. Difference calculating means for calculating a difference from the pixel value calculated by the pixel value calculating means; and cumulatively adding the difference calculated by the difference calculating means for each of the reference coordinates for each color component other than the reference color. Accumulative addition means, for each of the color components other than the reference color, such that the cumulative addition value accumulatively added by the accumulative addition means is minimized. The image processing apparatus according to claim 2 or 3, characterized in that it has a parameter changing means for changing the target transformation parameters, the. 5. The post-correction storage, wherein the writing control unit associates a pixel value of a coordinate converted by the coordinate conversion unit with a coordinate before the coordinate conversion for each color component other than the reference color. The image processing apparatus according to claim 2, wherein the image processing apparatus stores the image data.