Area-array camera radiation response non-uniformity autonomous coordination calibration method and system

Abstract

The invention discloses an area-array camera radiation response non-uniformity autonomous coordination calibration method and system, and relates to the area-array camera image processing technology field, and the method comprises the steps: calculating a distortion mean value picture based on a plurality of dark pictures shot by a to-be-calibrated area-array camera in a dark environment and a plurality of response distortion pictures shot by the to-be-calibrated area-array camera in a uniform brightness field, filtering to obtain a smooth picture, and determining a correction factor image; performing radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain a corrected image; judging whether the variance of the corrected image is smaller than the variance of the distorted mean image or not; if yes, recording the variance of the corrected image filtered this time, and filtering and correcting the corrected image again; and taking the correction factor image corresponding to the minimum variance value of the recorded correction picture as the effective calibration parameter of the radiation response non-uniformity. According to the invention, the technical problem that the brightness of the corrected image is not uniform in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of area array camera image processing, and in particular to an autonomous coordinated calibration method and system for area array camera radiation response inhomogeneity. Background Art

[0002] CMOS area array cameras are core components of modern computer vision and play a vital role in intelligent recognition, visual navigation, remote sensing and other fields. CMOS area array cameras capture light through two-dimensional array pixel units (CMOS pixels) and convert light signals into electrical signals to form digital images. Each pixel unit contains a photodiode and a readout circuit, which can independently complete the conversion and reading of light signals, thereby achieving high-speed and efficient image acquisition.

[0003] However, in the imaging process of CMOS area array cameras, the vignetting effect is a problem that cannot be ignored. The vignetting effect, also known as the dark corner effect or edge attenuation, refers to the phenomenon that the brightness of the edge or corner of the image is significantly lower than that of the central area. This brightness unevenness not only affects the overall visual effect of the image, but may also interfere with subsequent image processing and analysis. The causes of the vignetting effect are varied, mainly including the following aspects: 1) Optical system limitations: The lens and aperture design of the camera often limit the light passing through, resulting in a larger incident angle of the light at the edge, which is blocked by the lens edge or aperture, thereby reducing the amount of light reaching the edge pixels of the sensor; 2) Lens distortion: The lens will produce certain distortions during the imaging process, including barrel distortion and pincushion distortion, etc. These distortions will cause the pixel points at the edge of the image to offset from the actual object position, thereby affecting the brightness of the edge pixels; 3) Sensor characteristics: The CMOS sensor itself also has certain non-uniformity, including differences in pixel size and photoelectric conversion efficiency. These non-uniformities will be amplified during the imaging process, resulting in differences in the brightness of the edge pixels and the center pixels. 4) External environmental factors: such as the position of the light source and uneven distribution of light intensity, will also affect the brightness uniformity of the image.

[0004] In order to eliminate the influence of vignetting effect on image quality, researchers have proposed a variety of correction methods. However, these methods often have the following limitations: 1) Dependence on specific models: Many correction methods are based on specific mathematical models or assumptions, such as assuming that the vignetting effect is linearly or quadratically distributed. However, the vignetting effect in the actual imaging process is often more complex and difficult to accurately describe with a simple model. 2) Requires a large amount of experimental data: Some correction methods require a large number of experiments to obtain the statistical data of the vignetting effect and then perform corrections. This method is not only time-consuming and labor-intensive, but also difficult to ensure the universal applicability of the correction results. 3) Limited correction effect: Due to the various and intertwined causes of the vignetting effect, the existing correction methods can often only correct some factors, but cannot achieve comprehensive correction. Therefore, the corrected image still has a certain degree of brightness non-uniformity. Therefore, a more efficient and accurate autonomous coordinated calibration method is needed to solve this problem. Summary of the invention

[0005] In order to solve the technical problem in the prior art that the image after correction still has brightness non-uniformity, the embodiment of the present invention provides an autonomous coordinated calibration method and system for the non-uniformity of radiation response of an area array camera. The technical solution is as follows:

[0006] On the one hand, a method for autonomous coordinated calibration of radiation response non-uniformity of an area array camera is provided, the method comprising: calculating a distorted mean image of the area array camera to be calibrated based on a plurality of dark images taken by the area array camera to be calibrated in a lightless environment and a plurality of response distorted images taken in a uniform brightness field; filtering the distorted mean image based on a median filter to obtain a smoothed image, and determining a correction factor image based on pixel values ​​of the smoothed image; performing radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain a corrected image; The variance of the correction image and the variance of the distortion mean image are calculated respectively, and it is determined whether the variance of the correction image is smaller than the variance of the distortion mean image; if so, the variance of the correction image filtered this time is recorded, and the correction image is filtered again and the radiation response non-uniformity correction is performed on the correction image until the variance of the correction image is not smaller than the variance of the distorted uniform image or the correction image before the current filtering; the correction factor image corresponding to the minimum variance of the recorded correction image is used as the effective calibration parameter of the radiation response non-uniformity of the area array camera to be calibrated.

[0007] Optionally, based on a plurality of dark images taken by the area array camera to be calibrated in a lightless environment and a plurality of response distortion images taken in a uniform brightness field, a distortion mean image of the area array camera to be calibrated is calculated, including: obtaining a plurality of dark images taken by the area array camera to be calibrated in a lightless environment; calculating dark current correction parameters of the area array camera to be calibrated based on the plurality of dark images; obtaining a plurality of response distortion images taken by the area array camera to be calibrated in a uniform brightness field; and calculating a distortion mean image based on the plurality of response distortion images and the dark current correction parameters.

[0008] Optionally, calculating the dark current correction parameters of the area array camera to be calibrated based on the plurality of dark images includes:

[0009] Based on the following calculation formula, the average value of the plurality of dark images is calculated, and the average value of the plurality of dark images is used as the dark current correction parameter of the area array camera to be calibrated:

[0010]

[0011] In the formula, is the dark current correction parameter, is the coordinate of the kth dark image The pixel value of the position, n is the total number of the plurality of dark images, is the number of pixel rows and columns of the area array camera to be calibrated.

[0012] Optionally, calculating the distortion mean image based on the multiple response distortion images and the dark current correction parameter includes: subtracting the dark current correction parameter from the multiple response distortion images one by one to obtain a plurality of distortion corrected images; calculating the average value of the multiple distortion corrected images pixel by pixel according to the following calculation formula to obtain the distortion mean image:

[0013]

[0014] In the formula, is the distortion mean image at coordinates The pixel value of the location, is the kth response distortion image at coordinate The pixel value of the location, is the dark current correction parameter, and n is the total number of the multiple responsive distortion images.

[0015] Optionally, filtering the distorted mean image based on a median filter to obtain a smoothed image includes: based on the size of the median filter, expanding the pixel rows and columns of the distorted mean image by copying adjacent pixel values ​​to obtain an extended distorted mean image; sliding filtering the extended distorted mean image based on the median filter to obtain a filtered extended distorted mean image; deleting the expanded pixel rows and columns of the filtered extended distorted mean image to obtain a smoothed image.

[0016] Optionally, determining the correction factor image based on the pixel value of the smoothed image includes: performing pixel-by-pixel calculation using the ratio of the pixel value of the smoothed image to the maximum value of the smoothed image as the radiation response unevenness correction factor to obtain the correction factor image.

[0017] Optionally, the radiation response non-uniformity correction is performed on the distorted uniform image based on the correction factor image to obtain a corrected image, including: dividing the pixel value of the distorted mean image by the pixel value of the corresponding position of the correction factor image, performing the radiation response non-uniformity correction on the distorted mean image, and obtaining a corrected image.

[0018] On the other hand, an autonomous coordinated calibration system for radiation response non-uniformity of an area array camera is provided, comprising: a calculation module, a filtering module, a correction module, a judgment module, a recording module and a determination module; wherein the calculation module is used to calculate a distorted mean image of the area array camera to be calibrated based on a plurality of dark images taken by the area array camera to be calibrated in a lightless environment and a plurality of response distorted images taken in a uniform brightness field; the filtering module is used to filter the distorted mean image based on a median filter to obtain a smoothed image, and determine a correction factor image based on the pixel values ​​of the smoothed image; the correction module is used to perform radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain The correction image; the judging module is used to respectively calculate the variance of the correction image and the variance of the distortion mean image, and judge whether the variance of the correction image is smaller than the variance of the distortion mean image; the recording module is used to record the variance of the correction image filtered this time if the variance of the correction image is smaller than the variance of the distortion mean image, and filter and correct the radiation response non-uniformity of the correction image again until the variance of the correction image is not smaller than the variance of the distortion uniform image or the correction image before the current filtering; the determining module is used to use the correction factor image corresponding to the minimum variance of the recorded correction image as the effective calibration parameter of the radiation response non-uniformity of the area array camera to be calibrated.

[0019] On the other hand, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method provided in the embodiment of the present invention when executing the computer program.

[0020] On the other hand, a computer-readable storage medium is provided, in which a program code is stored. The program code can be called by a processor to execute the method provided in the embodiment of the present invention.

[0021] The embodiment of the present invention provides an autonomous coordinated calibration method and system for the non-uniformity of radiation response of an area array camera. The calibration parameters are automatically adjusted through an autonomous coordinated calibration algorithm to obtain the best correction factor. The present invention not only improves the accuracy and efficiency of the correction, but also reduces the correction cost, providing strong technical support for the wide application of CMOS area array cameras. At the same time, the present invention can effectively eliminate the vignetting effect in the imaging process of the CMOS area array camera, improve the brightness uniformity and overall quality of the image, and lay a solid foundation for subsequent image processing and analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 It is a flow chart of an autonomous coordinated calibration method for radiation response non-uniformity of an area array camera provided by an embodiment of the present invention;

[0024] Figure 2 It is a flow chart of another method for autonomous coordinated calibration of radiation response non-uniformity of an area array camera provided by an embodiment of the present invention;

[0025] Figure 3 is a schematic diagram of a radiation response inhomogeneity image provided by an embodiment of the present invention;

[0026] Figure 4 is based on Figure 3 The schematic diagram of three-dimensional visualization of pixel values ​​of the radiation response inhomogeneity image shown;

[0027] Figure 5 It is a three-dimensional visualization schematic diagram of effective calibration parameters of radiation response inhomogeneity obtained by an autonomous coordinated calibration method of radiation response inhomogeneity of an area array camera provided by an embodiment of the present invention;

[0028] Figure 6is a schematic diagram of three-dimensional visualization of uniform pixel values ​​after correction provided by an embodiment of the present invention;

[0029] Figure 7 is a schematic diagram of an original picture actually taken by a CMOS area array camera provided by an embodiment of the present invention;

[0030] Figure 8 is a schematic diagram of a picture corrected according to a calibration method provided by an embodiment of the present invention;

[0031] Fig. 9 is a schematic diagram of an autonomous coordinated calibration system for radiation response non-uniformity of an area array camera provided by an embodiment of the present invention;

[0032] Fig.10 It is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0034] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0035] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0036] Figure 1 FIG. 1 is a flow chart of a method for autonomous coordinated calibration of radiation response non-uniformity of an area array camera provided according to an embodiment of the present invention. Figure 1 As shown, the method specifically comprises the following steps:

[0037] Step S102, calculating the distortion mean value image of the area array camera to be calibrated based on a plurality of dark images taken by the area array camera to be calibrated in a dark environment and a plurality of response distortion images taken in a uniform brightness field.

[0038] Optionally, the area array camera to be calibrated includes a CMOS area array camera.

[0039] Preferably, the number of dark images taken is no less than three, and the number of corresponding distorted images is the same as the number of dark images.

[0040] Step S104, filtering the distorted mean image based on a median filter to obtain a smoothed image, and determining a correction factor image based on the pixel values ​​of the smoothed image.

[0041] Step S106, performing radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain a corrected image.

[0042] Step S108, respectively calculating the variance of the corrected image and the variance of the distorted mean image, and determining whether the variance of the corrected image is smaller than the variance of the distorted mean image.

[0043] Step S110, if the variance of the corrected image is smaller than the variance of the distorted mean image, the variance of the corrected image filtered this time is recorded, and the corrected image is filtered again and the radiation response non-uniformity correction is performed until the variance of the corrected image is not smaller than the variance of the distorted uniform image or the corrected image before the current filtering.

[0044] Specifically, if the variance of the corrected image is smaller than the variance of the distorted mean image, the corrected image is filtered, a new correction factor image is determined, and then the new correction factor image is used to correct the radiation response non-uniformity of the corrected image again to obtain a new corrected image. Finally, the variance of the new corrected image is compared with the variance of the corrected image before this filtering. If the variance of the newer corrected image is still smaller than the variance of the corrected image before this filtering, the above process is repeated again for the next round of filtering.

[0045] The embodiment of the present invention automatically adjusts and calibrates by taking the variance of the correction image as an autonomous coordination factor.

[0046] Step S112: using the correction factor image corresponding to the minimum variance value of the recorded correction image as an effective calibration parameter for the non-uniform radiation response of the area array camera to be calibrated.

[0047] Finally, when the area array camera to be calibrated is used in the subsequent process, the camera is calibrated using the effective calibration parameters of the finally obtained radiation response inhomogeneity.

[0048] Specifically, step S102 also includes the following steps:

[0049] Step S1021, obtaining a plurality of dark images taken by the area array camera to be calibrated in a dark environment, for example, taking images in a dark room with a lens cap on, to obtain dark images.

[0050] Step S1022, calculating dark current correction parameters of the area array camera to be calibrated based on the multiple dark images.

[0051] Specifically, based on the following calculation formula, the average value of multiple dark images is calculated, and the average value of the multiple dark images is used as the dark current correction parameter of the area array camera to be calibrated:

[0052]

[0053] In the formula, is the dark current correction parameter, is the coordinate of the kth dark image The pixel value of the position, n is the total number of dark images, is the number of pixel rows and columns of the area array camera to be calibrated.

[0054] Step S1023, obtaining a plurality of response distortion images taken by the area array camera to be calibrated in a uniform brightness field.

[0055] Step S1024, calculating the distortion mean image based on the multiple response distortion images and the dark current correction parameters.

[0056] Specifically, a plurality of response distortion images are subtracted from the dark current correction parameter one by one to obtain a plurality of distortion correction images; then, the average value of the plurality of distortion correction images is calculated pixel by pixel according to the following calculation formula to obtain a distortion mean image:

[0057]

[0058] In the formula, is the distortion mean image at coordinate The pixel value of the location, is the kth response distortion image at coordinate The pixel value of the location, is the dark current correction parameter, and n is the total number of multiple response distortion images.

[0059] Specifically, the filtering process in step S104 includes the following steps:

[0060] Step S1041, based on the size of the median filter, the pixel rows and columns of the distorted mean image are expanded by copying the values ​​of adjacent pixels to obtain an expanded distorted mean image;

[0061] For example, when the size of the median filter is 5×5, the distorted mean image is expanded by 2 rows and 2 columns to form an expanded distorted mean image. ;

[0062] Step S1042, performing sliding filtering on the extended distortion mean image based on a median filter to obtain a filtered extended distortion mean image;

[0063] Step S1043, deleting the expanded pixel rows of the filtered extended distortion mean image to obtain a smoothed image.

[0064] Specifically, the correction factor image calculation method in step S104 includes: taking the ratio of the pixel value of the smoothed image to the maximum value of the smoothed image as the radiation response non-uniformity correction factor to perform pixel-by-pixel calculation to obtain the correction factor image. The mathematical expression is as follows:

[0065]

[0066] In the formula, is the correction factor image, is the pixel coordinate, For smooth images.

[0067] Specifically, step S106 further includes: dividing the pixel value of the distortion mean image by the pixel value of the corresponding position of the correction factor image, performing radiation response non-uniformity correction on the distortion mean image, and obtaining a corrected image. The mathematical expression is as follows:

[0068]

[0069] In the formula, To correct the image in coordinates The cell value of the location.

[0070] Specifically, in step S108, the variance of the correction image and the variance of the distortion mean image are calculated as follows:

[0071]

[0072]

[0073] In the formula, To correct the variance of the image, is the variance of the distorted mean image, and mean() means taking the average value.

[0074] Figure 2 FIG. 4 is a flow chart of another method for autonomous coordinated calibration of radiation response non-uniformity of an area array camera provided according to an embodiment of the present invention. Figure 2 As shown, in an optional implementation manner provided by an embodiment of the present invention, the method further includes the following steps:

[0075] Step 1: With the lens cap on or in a dark room, use pixel rows as The camera to be calibrated takes at least three (1, 2, 3, ..., n) dark images in succession. , calculate the average value of multiple dark photos as the dark current correction parameter ;

[0076] Step 2: Use the camera to be calibrated to continuously take at least three (1, 2, 3, ..., n) response distortion images of uniform brightness field. , subtract dark current correction parameters from each photo , and pixel by pixel Calculate the average value of multiple images to obtain the distortion mean image ;

[0077] Step 3: Construct a 5×5 median filter and expand the pixel rows and columns of the distorted mean image by copying the values ​​of adjacent pixels to form a new response distorted image. ;

[0078] Step 4: Median filter and expanded response distortion image Perform sliding operation to generate filtered smooth images ;

[0079]

[0080] Step 5: Delete the smoothed image The 2 rows and 2 columns of pixels that extend outside the rows and columns restore the original size of the image to ;

[0081] Step 6: Smooth the image pixel values The maximum value of the smoothed image pixel value The ratio of is used as the correction factor for the non-uniformity of radiation response , calculate pixel by pixel to get the correction factor image ;

[0082] Step 7: Divide the pixel value of the original distorted mean image by the pixel value of the corresponding position of the correction factor image, and perform radiation response non-uniformity correction on the original distorted mean image to obtain the corrected image. ;

[0083] Step 8: Calculate the variance of the corrected image and the variance of the distortion mean image respectively;

[0084] Step 9: Compare the variance of the corrected images (Right now Figure 2 The variance coordination factor of the corrected image in Figure 2 The variance of the pre-corrected image in If the correction image variance is less than the distortion mean image variance, record the number of times of this filtering and the correction image variance, and replace the filtering object in the third step - the distortion mean image with the correction image, and then repeat the third step to the eighth step until the correction image variance is greater than or equal to the distortion mean image variance;

[0085] Step 10: Using the variance of the correction image as the autonomous coordination factor, statistically analyze the variance of the correction image, and use the correction factor image used when the variance of the correction image is the smallest as the effective calibration parameter of the radiation response inhomogeneity.

[0086] Figure 3 is a schematic diagram of a radiation response inhomogeneity image provided according to an embodiment of the present invention, Figure 4 is based on Figure 3 The three-dimensional visualization diagram of the pixel values ​​of the radiation response inhomogeneity image is shown. Figure 5 The three-dimensional visualization diagram of effective calibration parameters of radiation response inhomogeneity obtained by an autonomous coordinated calibration method for radiation response inhomogeneity of an area array camera provided by an embodiment of the present invention. Figure 3 The radiation response inhomogeneity image shown in FIG. 1 is subjected to pixel value correction to obtain a three-dimensional visualization diagram of uniform pixel values ​​after correction. Figure 6 shown.

[0087] Figure 7 is a schematic diagram of an original picture actually taken by a CMOS area array camera provided according to an embodiment of the present invention, Figure 8 It is a schematic diagram of a picture corrected by the calibration method provided by an embodiment of the present invention.

[0088] Depend on Figure 4 and Figure 6 The comparison and Figure 7 and Figure 8 It can be seen from the comparison that the autonomous coordinated calibration method for the non-uniformity of radiation response of the area array camera provided by the embodiment of the present invention can effectively eliminate the vignetting effect in the imaging process of the CMOS area array camera and improve the brightness uniformity and overall quality of the image.

[0089] Fig. 9 FIG. 1 is a schematic diagram of an autonomous coordinated calibration system for the non-uniformity of radiation response of an area array camera provided according to an embodiment of the present invention. Fig. 9 As shown, it includes: a calculation module 10, a filtering module 20, a correction module 30, a judgment module 40, a recording module 50 and a determination module 60.

[0090] Specifically, the calculation module 10 is used to calculate the distortion mean value image of the area array camera to be calibrated based on a plurality of dark images taken by the area array camera to be calibrated in a dark environment and a plurality of response distortion images taken in a uniform brightness field;

[0091] A filtering module 20, configured to filter the distorted mean image based on a median filter to obtain a smoothed image, and determine a correction factor image based on pixel values ​​of the smoothed image;

[0092] A correction module 30, for performing radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain a corrected image;

[0093] A judgment module 40, for respectively calculating the variance of the corrected image and the variance of the distorted mean image, and judging whether the variance of the corrected image is smaller than the variance of the distorted mean image;

[0094] A recording module 50 is used to record the variance of the corrected image of this filtering if the variance of the corrected image is smaller than the variance of the distorted mean image, and to filter and correct the radiation response non-uniformity of the corrected image again until the variance of the corrected image is not smaller than the variance of the distorted uniform image or the corrected image before this filtering;

[0095] The determination module 60 is used to use the correction factor image corresponding to the minimum variance value of the recorded correction image as the effective calibration parameter of the radiation response non-uniformity of the area array camera to be calibrated.

[0096] Specifically, the computing module 10 is further used for:

[0097] Obtain multiple dark images taken by the area array camera to be calibrated in a dark environment;

[0098] Based on the following calculation formula, the average value of multiple dark images is calculated, and the average value of multiple dark images is used as the dark current correction parameter of the area array camera to be calibrated:

[0099]

[0100] Acquire multiple response distortion images taken by the area array camera to be calibrated in a uniform brightness field;

[0101] Subtracting dark current correction parameters from a plurality of response distortion images one by one to obtain a plurality of distortion correction images;

[0102] For multiple distortion-corrected images, the average value is calculated pixel by pixel according to the following calculation formula to obtain the distortion mean image:

[0103]

[0104] Specifically, the filtering module 20 is further used for:

[0105] Based on the size of the median filter, the pixel rows and columns of the distorted mean image are expanded by copying the values ​​of adjacent pixels to obtain an extended distorted mean image.

[0106] Performing sliding filtering on the extended distortion mean image based on a median filter to obtain a filtered extended distortion mean image;

[0107] Deleting the dilated pixel rows of the filtered extended distorted mean image to obtain a smoothed image;

[0108] The ratio of the pixel value of the smoothed image to the maximum value of the smoothed image is used as the correction factor for the non-uniform radiation response and is calculated pixel by pixel to obtain a correction factor image.

[0109] Specifically, the correction module 30 is further used to: perform radiation response non-uniformity correction on the distorted mean value image by dividing the pixel value of the distorted mean value image by the pixel value of the corresponding position of the correction factor image to obtain a corrected image.

[0110] It can be seen from the above description that the embodiment of the present invention provides a method and system for autonomous coordinated calibration of radiation response non-uniformity of an area array camera, which has the following technical effects compared with the prior art:

[0111] (1) Autonomous coordinated calibration: The present invention can automatically determine the calibration coordination parameters with the best correction effect according to the vignetting characteristics of the CMOS area array camera to obtain the best correction factor.

[0112] (2) Multi-factor comprehensive correction: The present invention comprehensively considers multiple factors such as aperture size, lens type, and imaging sensor size to comprehensively correct the vignetting effect and achieve consistency in the radiation response of CMOS pixels.

[0113] (3) High efficiency and accuracy: The present invention improves the correction efficiency and accuracy and reduces the correction cost by optimizing algorithms and data processing technology.

[0114] Fig.10 is a schematic diagram of an electronic device provided according to an embodiment of the present invention. Fig.10 As shown, the electronic device includes: a memory 1001, a processor 1002, and a computer program stored in the memory 1001 and executable on the processor 1002. When the processor 1002 executes the computer program, the method provided in the embodiment of the present invention is implemented.

[0115] The present invention further provides a computer-readable storage medium, in which program codes are stored. The program codes can be called by a processor to execute the method provided in the embodiment of the present invention.

[0116] It should be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0117] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0118] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0119] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0120] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0121] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0122] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0124] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0125] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An autonomous coordinated calibration method for the non-uniformity of radiation response of an area array camera, characterized in that: The method comprises: Calculate the distortion mean value image of the area array camera to be calibrated based on a plurality of dark images taken by the area array camera to be calibrated in a dark environment and a plurality of response distortion images taken in a uniform brightness field; Filtering the distorted mean image based on a median filter to obtain a smoothed image, and determining a correction factor image based on pixel values ​​of the smoothed image; Performing radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain a corrected image; Calculating the variance of the corrected image and the variance of the distorted mean image respectively, and determining whether the variance of the corrected image is smaller than the variance of the distorted mean image; If yes, the variance of the corrected image of this filtering is recorded, and the corrected image is filtered again and corrected for the non-uniformity of the radiation response until the variance of the corrected image is not less than the variance of the distorted uniform image or the corrected image before this filtering; The correction factor image corresponding to the minimum variance value of the recorded correction image is used as an effective calibration parameter for the non-uniform radiation response of the area array camera to be calibrated.

2. The method according to claim 1, characterized in that Based on a plurality of dark images taken by the area array camera to be calibrated in a dark environment and a plurality of response distortion images taken in a uniform brightness field, a distortion mean image of the area array camera to be calibrated is calculated, including: Obtain multiple dark images taken by the area array camera to be calibrated in a dark environment; Calculating dark current correction parameters of the area array camera to be calibrated based on the multiple dark images; Acquire a plurality of response distortion images taken by the area array camera to be calibrated in a uniform brightness field; A distortion mean image is calculated based on the multiple response distortion images and the dark current correction parameters.

3. The method according to claim 2, characterized in that Calculating dark current correction parameters of the area array camera to be calibrated based on the plurality of dark images includes: Based on the following calculation formula, the average value of the plurality of dark images is calculated, and the average value of the plurality of dark images is used as the dark current correction parameter of the area array camera to be calibrated: ； In the formula, is the dark current correction parameter, is the coordinate of the kth dark image The pixel value of the position, n is the total number of the plurality of dark images, is the number of pixel rows and columns of the area array camera to be calibrated.

4. The method according to claim 2, characterized in that: Calculating a distortion mean value image based on the plurality of response distortion images and the dark current correction parameter comprises: Subtracting the dark current correction parameter from the plurality of response distortion images one by one to obtain a plurality of distortion correction images; The average value of the plurality of distortion-corrected images is calculated pixel by pixel according to the following calculation formula to obtain a distortion mean image: ； In the formula, is the distortion mean image at coordinates The pixel value of the location, is the kth response distortion image at coordinate The pixel value of the location, is the dark current correction parameter, and n is the total number of the plurality of responsive distortion images.

5. The method according to claim 1, characterized in that: Filtering the distorted mean image based on a median filter to obtain a smoothed image includes: Based on the size of the median filter, the distorted mean image is expanded in pixel rows and columns by copying the values ​​of adjacent pixels to obtain an expanded distorted mean image; Performing sliding filtering on the extended distortion mean image based on the median filter to obtain a filtered extended distortion mean image; The dilated pixel rows of the filtered extended distortion mean image are deleted to obtain a smoothed image.

6. The method according to claim 1, characterized in that Determining a correction factor image based on the pixel values ​​of the smoothed image includes: The ratio of the pixel value of the smoothed image to the maximum value of the smoothed image is used as a correction factor for the non-uniform radiation response to perform pixel-by-pixel calculation to obtain a correction factor image.

7. The method according to claim 1, characterized in that The method further comprises: performing radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain a corrected image, comprising: The pixel value of the distortion mean value image is divided by the pixel value of the corresponding position of the correction factor image, and the radiation response non-uniformity correction is performed on the distortion mean value image to obtain a corrected image.

8. An autonomous coordinated calibration system for the non-uniformity of radiation response of an area array camera, characterized in that: include: Calculation module, filtering module, correction module, judgment module, recording module and determination module; wherein, The calculation module is used to calculate the distortion mean value image of the area array camera to be calibrated based on a plurality of dark images taken by the area array camera to be calibrated in a dark environment and a plurality of response distortion images taken in a uniform brightness field; The filtering module is used to filter the distorted mean image based on a median filter to obtain a smoothed image, and determine a correction factor image based on pixel values ​​of the smoothed image; The correction module is used to perform radiation response non-uniformity correction on the distorted uniform image based on the correction factor image to obtain a corrected image; The judging module is used to respectively calculate the variance of the corrected image and the variance of the distorted mean image, and judge whether the variance of the corrected image is smaller than the variance of the distorted mean image; The recording module is used for recording the variance of the corrected image of this filtering if the variance of the corrected image is smaller than the variance of the distorted mean image, and filtering and radiant response non-uniformity correction are performed on the corrected image again until the variance of the corrected image is not smaller than the variance of the distorted uniform image or the corrected image before this filtering; The determination module is used to use the correction factor image corresponding to the minimum variance value of the recorded correction image as the effective calibration parameter of the radiation response inhomogeneity of the area array camera to be calibrated.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, which can be called by a processor to execute the method according to any one of claims 1 to 7.

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