An autonomous coordination calibration method and system for non-uniformity of linear array camera radiation response

Abstract

The present invention discloses a method and system for autonomously coordinated calibration of the radiation response non-uniformity of an area array camera, which relates to the technical field of area array camera image processing and includes: calculating a distorted mean image based on multiple dark images captured by the area array camera to be calibrated in a lightless environment and multiple response distorted images captured in a uniform brightness field, then performing filtering to obtain a smoothed image, 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; determining whether the variance of the corrected image is less than the variance of the distorted mean image; if so, recording the variance of the corrected image of this filtering, and performing filtering and correction on the corrected image again; using the correction factor image corresponding to the minimum value of the variance of the recorded corrected image as the effective calibration parameter for the radiation response. The present invention alleviates the technical problem that the brightness non-uniformity still exists in the corrected image in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of area array camera image processing, and particularly to an autonomous coordination calibration method and system for the non-uniformity of the radiation response of an area array camera. Background Art

[0002] A CMOS area array camera is a core component of modern computer vision and plays a crucial role in fields such as intelligent recognition, visual navigation, and remote sensing detection. The CMOS area array camera captures light through pixel units (i.e., CMOS pixels) arranged in a two-dimensional array, converts the optical signal into an electrical signal, and then forms a digital image. Each pixel unit contains a photodiode and a readout circuit, which can independently complete the conversion and reading of the optical signal, thereby achieving high-speed and efficient image acquisition.

[0003] However, in the imaging process of a CMOS area array camera, 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 image edge or corner is significantly lower than that of the central region. This non-uniformity of brightness not only affects the overall visual effect of the image but may also interfere with subsequent image processing and analysis. The reasons for the vignetting effect are diverse and mainly include the following aspects: 1) Optical system limitations: The lens and aperture design of the camera often limit the passing light, resulting in a larger incident angle of light at the edge part, being blocked by the lens edge or aperture, thus reducing the amount of light reaching the pixels at the sensor edge; 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 image edge to deviate from the actual object position, thereby affecting the brightness of the edge pixels; 3) Sensor characteristics: There are also certain non-uniformities in the CMOS sensor itself, including pixel size differences, photoelectric conversion efficiency differences, etc. These non-uniformities will be amplified during the imaging process, resulting in a difference in brightness between the edge pixels and the central pixels. 4) External environmental factors: Such as the light source position, uneven light intensity distribution, etc., will also affect the brightness uniformity of the image.

[0004] To eliminate the influence of vignetting effect on image quality, researchers have proposed various 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) Requirement for a large amount of experimental data: Some correction methods need to obtain statistical data on the vignetting effect through a large number of experiments for correction. This method is not only time-consuming and laborious but also difficult to ensure the general applicability of the correction results. 3) Limited correction effect: Due to the diverse and intertwined causes of the vignetting effect, existing correction methods can often only correct some factors and cannot achieve comprehensive correction. Therefore, there is still a certain degree of brightness non-uniformity in the corrected image. Therefore, a more efficient and accurate autonomous coordination calibration method is needed to solve this problem. Summary of the Invention

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

[0006] On the one hand, a method for autonomous coordination calibration of the non-uniformity of the radiation response of an area array camera is provided. The method includes: calculating a distorted mean image of the area array camera to be calibrated based on multiple dark images taken by the area array camera to be calibrated in a lightless environment and multiple response distorted images taken in a uniform brightness field; filtering the distorted mean image with a median filter to obtain a smoothed image, and determining a correction factor image based on the pixel values of the smoothed image; performing non-uniformity correction of the radiation response on the distorted mean 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 less than the variance of the distorted mean image; if so, recording the variance of the corrected image of this filtering, and performing filtering and non-uniformity correction of the radiation response on the corrected image again until the variance of the corrected image is not less than the variance of the distorted mean image or the variance of the corrected image before this filtering; using the correction factor image corresponding to the minimum variance of the recorded corrected image as the effective calibration parameter for the non-uniformity of the radiation response of the area array camera to be calibrated.

[0007] Optionally, based on multiple dark images captured by the area array camera to be calibrated in a lightless environment and multiple response distortion images captured in a uniform brightness field, calculating a distortion mean image of the area array camera to be calibrated includes: obtaining multiple dark images captured 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 multiple dark images; obtaining multiple response distortion images captured by the area array camera to be calibrated in a uniform brightness field; and calculating a distortion mean image based on the multiple 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 multiple dark images includes:

[0009] Calculating an average value of the multiple dark images based on the following calculation formula, and taking the average value of the multiple dark images as the dark current correction parameters of the area array camera to be calibrated:

[0010]

[0011] In the formula, is the dark current correction parameter, is the pixel value at the position with coordinates in the k-th dark image, n is the total number of the multiple dark images, is the number of pixel rows and columns of the area array camera to be calibrated.

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

[0013]

[0014] In the formula, is the pixel value of the distortion mean image at the position with coordinates ; is the pixel value of the k-th response distortion image at the position with coordinates ; is the dark current correction parameter, and m is the total number of the multiple response distortion images.

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

[0016] Optionally, determining a correction factor image based on the pixel values of the smoothed image, including: calculating a radiation response non-uniformity correction factor for each pixel as the ratio of the pixel value of the smoothed image to the maximum value of the smoothed image to obtain a correction factor image.

[0017] Optionally, correcting the radiation response non-uniformity of the distorted mean 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 at the corresponding position of the correction factor image to correct the radiation response non-uniformity of the distorted mean image to obtain a corrected image.

[0018] On the other hand, a self-coordinated calibration system for radiation response non-uniformity of an area array camera is also provided, including: a calculation module, a filtering module, a correction module, a judgment module, a recording module, and a determination module; wherein, the calculation module is configured to calculate the distorted mean image of the area array camera to be calibrated based on multiple dark images captured by the area array camera to be calibrated in a lightless environment and multiple response distorted images captured in a uniform brightness field; the filtering module is 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 the pixel values of the smoothed image; the correction module is configured to correct the radiation response non-uniformity of the distorted mean image based on the correction factor image to obtain a corrected image; the judgment module is configured to calculate the variance of the corrected image and the variance of the distorted mean image respectively, and judge whether the variance of the corrected image is less than the variance of the distorted mean image; the recording module is configured to, if the variance of the corrected image is less than the variance of the distorted mean image, record the variance of the corrected image of this filtering, and filter and correct the radiation response non-uniformity of the corrected image again until the variance of the corrected image is not less than the variance of the distorted mean image or the variance of the corrected image before this filtering; the determination module is configured to use the correction factor image corresponding to the minimum variance of the recorded corrected image as the effective calibration parameter for the radiation response non-uniformity of the area array camera to be calibrated.

[0019] On the other hand, an electronic device is also provided, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the computer program, the method provided in the embodiment of the present invention is implemented.

[0020] On the other hand, a computer-readable storage medium is also provided, in which program code is stored, and 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 a method and system for autonomous coordinated calibration of the radiation response non-uniformity of a planar array camera. By an autonomous coordinated calibration algorithm, calibration parameters are automatically adjusted to obtain the best correction factor. The present invention not only improves the accuracy and efficiency of calibration, but also reduces the calibration cost, providing strong technical support for the wide application of CMOS planar array cameras. At the same time, the present invention can effectively eliminate the vignetting effect in the imaging process of CMOS planar array cameras, improve the brightness uniformity and overall quality of images, 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 will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

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

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

[0025] Figure 3 is a schematic diagram of a photographic film with non-uniform radiation response provided by an embodiment of the present invention;

[0026] Figure 4 is based on Figure 3 a three-dimensional visualization schematic diagram of the pixel values of the photographic film with non-uniform radiation response shown;

[0027] Figure 5 is a three-dimensional visualization schematic diagram of the effective calibration parameters of the radiation response non-uniformity obtained based on a method for autonomous coordinated calibration of the radiation response non-uniformity of a planar array camera provided by an embodiment of the present invention;

[0028] Figure 63D visualization diagram of uniform pixel values after correction provided by an embodiment of the present invention;

[0029] Figure 7 2 is a schematic diagram of an original image actually taken by a CMOS area array camera provided by an embodiment of the present invention;

[0030] Figure 8 1 is a schematic diagram of a photograph corrected according to a calibration method provided in an embodiment of the present invention;

[0031] Figure 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] Figure 10 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 an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0035] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, 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 non-uniform radiation response of an area array camera according to an embodiment of the present invention. Figure 1 As shown, the method specifically includes the following steps:

[0037] Step S102 : calculating a distortion 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 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: 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.

[0041] Step S106: Perform non-uniformity correction of the radiation response on the distorted mean image based on the correction factor image to obtain a corrected image.

[0042] Step S108: Calculate the variance of the corrected image and the variance of the distorted mean image respectively, and determine whether the variance of the corrected image is less than the variance of the distorted mean image.

[0043] Step S110: If the variance of the corrected image is less than the variance of the distorted mean image, record the variance of the corrected image for this filtering, and perform filtering and non-uniformity correction of the radiation response on the corrected image again until the variance of the corrected image is not less than the variance of the distorted mean image or the variance of the corrected image before this filtering.

[0044] Specifically, if the variance of the corrected image is less than the variance of the distorted mean image, filter the corrected image, determine a new correction factor image, and then perform non-uniformity correction of the radiation response on the corrected image again using the new correction factor image to obtain a new corrected image. Finally, compare the variance of the new corrected image with the variance of the corrected image before this filtering. If the variance of the newer corrected image is still less than the variance of the corrected image before this filtering, repeat the above process again for the next round of filtering.

[0045] In the embodiment of the present invention, the variance of the corrected image is used as an autonomous coordination factor for automatic adjustment and calibration.

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

[0047] Finally, when using the area array camera to be calibrated subsequently, perform camera calibration using the finally obtained effective calibration parameter for non-uniformity of the radiation response.

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

[0049] Step S1021: Obtain multiple dark images taken by the area array camera to be calibrated in a lightless environment. For example, take pictures with the lens cap covered or in a darkroom environment to obtain dark images.

[0050] Step S1022: Calculate the dark current correction parameter of the area array camera to be calibrated based on the multiple dark images.

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

[0052]

[0053] Wherein, is the dark current correction parameter, is the pixel value at the position of in the k-th dark image, and n is the total number of multiple dark images, is the number of pixel rows and columns of the area array camera to be calibrated.

[0054] Step S1023: Obtain multiple response distortion images captured by the area array camera to be calibrated under a uniform brightness field.

[0055] Step S1024: Calculate the distortion mean image based on the multiple response distortion images and the dark current correction parameter.

[0056] Specifically, subtract the dark current correction parameter from each of the multiple response distortion images to obtain multiple distortion correction images; then calculate the average value of each pixel of the multiple distortion correction images according to the following calculation formula to obtain the distortion mean image:

[0057]

[0058] Wherein, is the pixel value of the distortion mean image at the coordinate position, is the pixel value of the k-th response distortion image at the coordinate position, is the dark current correction parameter, and m 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, expand the pixel rows and columns of the distortion mean image by copying the values of adjacent pixels to obtain an extended distortion mean image;

[0061] For example, when the size of the median filter is 5×5, expand 2 rows and 2 columns on the outside of the rows and columns of the distortion mean image to form the extended distortion mean image ;

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

[0063] Step S1043: Delete the expanded pixel rows and columns of the filtered extended distortion mean image to obtain the smoothed image.

[0064] Specifically, the method for calculating the correction factor image in step S104 includes: calculating pixel by pixel with the ratio of the pixel value of the smoothed photo to the maximum value of the smoothed photo as the radiation response non-uniformity correction factor 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, is the smoothed photo.

[0067] Specifically, step S106 further includes: dividing the pixel value of the distorted mean photo by the pixel value at the corresponding position of the correction factor image to perform radiation response non-uniformity correction on the distorted mean photo to obtain the corrected photo. The mathematical expression is as follows:

[0068]

[0069] In the formula, is the pixel value of the corrected photo at the coordinate position.

[0070] Specifically, in step S108, the calculation formulas for the variance of the corrected photo and the variance of the distorted mean photo are as follows:

[0071]

[0072]

[0073] In the formula, is the variance of the corrected photo, is the variance of the distorted mean photo, and mean() represents taking the average value.

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

[0075] First step: In an environment with a lens cap on or in a darkroom, use a camera to be calibrated with a pixel row and column of to continuously take no less than three (1, 2, 3,..., n) dark photos , and calculate the average value of multiple dark photos as the dark current correction parameter ;

[0076] Second step: Use the camera to be calibrated to continuously take no less than three (1, 2, 3,..., n) response distorted photos of a uniform brightness field , subtract the dark current correction parameter from each photo , and calculate the average value of multiple photos pixel by pixel to obtain the distorted mean photo ;

[0077] Step 3: Construct a median filter with a size of 5×5, and at the same time expand 2 rows and 2 columns on the outside of the pixel rows and columns of the distorted mean photo by copying the values of adjacent pixels to form a new response distorted photo ;

[0078] Step 4: Perform a sliding operation on the median filter and the expanded response distorted photo to generate a smoothed photo after filtering ;

[0079]

[0080] Step 5: Delete the 2 rows and 2 columns of pixels expanded on the outside of the rows and columns of the smoothed photo, and restore the original size of the photo to ; ;

[0081] Step 6: Use the ratio of the pixel value of the smoothed photo to the maximum value of the pixel value of the smoothed photo as the radiation response non-uniformity correction factor and calculate the correction factor image pixel by pixel ;

[0082] Step 7: Divide the pixel value of the original distorted mean photo by the pixel at the corresponding position of the correction factor image to correct the radiation response non-uniformity of the original distorted mean photo to obtain the corrected photo ;

[0083] Step 8: Calculate the variance of the corrected photo and the variance of the distorted mean photo respectively;

[0084] Step 9: Compare the variance of the corrected photo (i.e., the corrected photo variance coordination factor in Figure 2 ) with the variance of the distorted mean photo (i.e., the photo before correction in Figure 2 ) . If the variance of the corrected photo is less than the variance of the distorted mean photo, record the number of times of this filtering and the variance of the corrected photo, and replace the filtering object in Step 3 - the distorted mean photo with the corrected photo, and then repeat Steps 3 - 8 until the variance of the corrected photo is greater than or equal to the variance of the distorted mean photo;

[0085] Step 10: Use the variance of the calibrated image as the autonomous coordination factor, conduct statistical analysis on the variance of the calibrated image, and use the calibration factor image adopted when the variance of the calibrated image is the smallest as the effective calibration parameter for radiation response non-uniformity.

[0086] Figure 3 It is a schematic diagram of a radiation response non-uniformity image provided by an embodiment of the present invention. Figure 4 It is based on Figure 3 The three-dimensional visualization schematic diagram of the pixel values of the radiation response non-uniformity image shown. Figure 5 It is a three-dimensional visualization schematic diagram of the effective calibration parameter for radiation response non-uniformity obtained based on an autonomous coordination calibration method for the radiation response non-uniformity of an area array camera provided by an embodiment of the present invention. Use the effective calibration parameter for radiation response non-uniformity obtained by the method provided by the embodiment of the present invention to Figure 3 Perform pixel value correction on the radiation response non-uniformity image shown, and obtain the three-dimensional visualization schematic diagram of the corrected uniform pixel values as shown in Figure 6 shown.

[0087] Figure 7 It is a schematic diagram of the original image actually captured by a CMOS area array camera provided by an embodiment of the present invention. Figure 8 It is a schematic diagram of the image after correction according to the calibration method provided by an embodiment of the present invention provided by an embodiment of the present invention.

[0088] From Figure 4 and Figure 6 comparison, as well as Figure 7 and Figure 8 comparison, it can be seen that the autonomous coordination calibration method for the radiation response non-uniformity 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] Figure 9 It is a schematic diagram of an autonomous coordination calibration system for the radiation response non-uniformity of an area array camera provided by an embodiment of the present invention. As shown in Figure 9 shown, it includes: calculation module 10, filtering module 20, correction module 30, judgment module 40, recording module 50 and determination module 60.

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

[0091] The filtering module 20 is used to filter the distortion mean image based on a median filter to obtain a smoothed image, and determine the calibration factor image based on the pixel values of the smoothed image.

[0092] A calibration module 30, configured to perform non-uniformity correction of radiation response on the distorted mean image based on the calibration factor image to obtain a calibrated image;

[0093] A judgment module 40, configured to calculate the variance of the calibrated image and the variance of the distorted mean image respectively, and judge whether the variance of the calibrated image is less than the variance of the distorted mean image;

[0094] A recording module 50, configured to record the variance of the calibrated image of this filtering if the variance of the calibrated image is less than the variance of the distorted mean image, and perform filtering and non-uniformity correction of radiation response on the calibrated image again until the variance of the calibrated image is not less than the variance of the distorted mean image or the variance of the calibrated image before this filtering;

[0095] A determination module 60, configured to use the calibration factor image corresponding to the minimum variance of the recorded calibrated image as the effective calibration parameter for non-uniformity of radiation response of the to-be-calibrated area array camera.

[0096] Specifically, the calculation module 10 is further configured to:

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

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

[0099]

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

[0101] Subtract the dark current correction parameter from each of the multiple response distorted images one by one to obtain multiple distorted corrected images;

[0102] Calculate the average value of each pixel of the multiple distorted corrected images according to the following calculation formula to obtain a distorted mean image:

[0103]

[0104] Specifically, the filtering module 20 is further configured to:

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

[0106] Perform sliding filtering on the expanded distorted mean image based on the median filter to obtain a filtered expanded distorted mean image;

[0107] Delete the expanded pixel rows and columns of the extended distorted mean photo after filtering to obtain a smoothed photo;

[0108] Use the ratio of the pixel value of the smoothed photo to the maximum value of the smoothed photo as the radiation response non-uniformity correction factor for pixel-by-pixel calculation to obtain a correction factor image.

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

[0110] As can be seen from the above description, the embodiments of the present invention provide a method and system for autonomous coordinated calibration of radiation response non-uniformity of an area array camera. Compared with the prior art, it has the following technical effects:

[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) Comprehensive multi-factor correction: The present invention comprehensively considers various factors such as the aperture size, lens type, and imaging sensor size to comprehensively correct the vignetting effect and achieve the consistency of 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 through optimized algorithms and data processing technologies.

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

[0115] The present invention also provides a computer-readable storage medium. The computer-readable storage medium stores program codes, and the program codes can be called by the processor to execute the method provided by the embodiment of the present invention.

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

[0117] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any combination thereof. When implemented using 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 processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. 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.) means. 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 a data center that contains a collection of one or more available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, or a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

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

[0119] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0120] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0121] In 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 merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

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

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

[0124] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0125] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An autonomous coordinated calibration method for non-uniformity of the radiation response of a planar array camera, characterized in that The method includes: Based on multiple dark images captured by the area array camera to be calibrated in a lightless environment and multiple response distortion images captured in a uniform brightness field, calculating the distortion mean image of the area array camera to be calibrated; Filtering the distortion 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; Performing non-uniform radiation response correction on the distortion mean image based on the correction factor image to obtain a corrected image; Calculating the variance of the corrected image and the variance of the distortion mean image respectively, and determining whether the variance of the corrected image is less than the variance of the distortion mean image; If so, recording the variance of the corrected image of this filtering, and performing filtering and non-uniform radiation response correction on the corrected image again until the variance of the corrected image is not less than the variance of the distortion mean image or the variance of the corrected image before this filtering; Taking the correction factor image corresponding to the minimum variance of the recorded corrected image as the effective calibration parameter for non-uniform radiation response of the area array camera to be calibrated.

2. The method according to claim 1, wherein Based on multiple dark images captured by the area array camera to be calibrated in a lightless environment and multiple response distortion images captured in a uniform brightness field, calculating the distortion mean image of the area array camera to be calibrated, including: Obtaining multiple dark images captured by the area array camera to be calibrated in a lightless environment; Calculating the dark current correction parameter of the area array camera to be calibrated based on the multiple dark images; Obtaining multiple response distortion images captured by the area array camera to be calibrated in a uniform brightness field; Calculating the distortion mean image based on the multiple response distortion images and the dark current correction parameter.

3. The method according to claim 2, wherein Calculating the dark current correction parameter of the area array camera to be calibrated based on the multiple dark images, including: Based on the following calculation formula, calculating the average value of the multiple dark images, and taking the average value of the multiple dark images as the dark current correction parameter of the area array camera to be calibrated: ; Wherein, is the dark current correction parameter, is the pixel value at the position with coordinates in the k-th dark image, n is the total number of the multiple 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 the distortion mean image based on the multiple response distortion images and the dark current correction parameter, including: Subtracting the dark current correction parameter from each of the multiple response distortion images one by one to obtain multiple distortion-corrected images; Calculating the average value of each pixel of the multiple distortion-corrected images according to the following calculation formula to obtain the distortion mean image: ; In the formula, is the pixel value of the distorted mean image at the coordinate position, is the pixel value of the k-th response distorted image at the coordinate position, is the dark current correction parameter, and m is the total number of the multiple response distorted images.

5. The method according to claim 1, wherein Filtering the distortion mean image based on a median filter to obtain a smoothed image, including: Based on the size of the median filter, expanding the pixel rows and columns of the distortion mean image by copying adjacent pixel values to obtain an expanded distortion mean image; Performing sliding filtering on the expanded distortion mean image based on the median filter to obtain a filtered expanded distortion mean image; Deleting the expanded pixel rows and columns of the filtered expanded distortion mean image to obtain a smoothed photo.

6. The method according to claim 1, wherein Determining a correction factor image based on the pixel values of the smoothed image, including: Calculating the radiation response non-uniformity correction factor as the ratio of the pixel value of the smoothed image to the maximum value of the smoothed image for each pixel to obtain a correction factor image.

7. The method according to claim 1, characterized in that Performing non-uniform radiation response correction on the distortion mean image based on the correction factor image to obtain a corrected image, including: Dividing the pixel values of the distorted mean image by the pixel values at the corresponding positions of the correction factor image to perform non-uniformity correction of the radiation response for the distorted mean image, thereby obtaining a corrected image.

8. An autonomous coordinated calibration system for the non-uniformity of the radiation response of an area array camera, characterized in that, Including: a calculation module, a filtering module, a correction module, a judgment module, a recording module, and a determination module; wherein, the calculation module is configured to calculate the distorted mean image of the to-be-calibrated area array camera based on multiple dark images captured by the to-be-calibrated area array camera in a lightless environment and multiple response distorted images captured in a uniform brightness field; the filtering module is 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 the pixel values of the smoothed image; the correction module is configured to perform non-uniformity correction of the radiation response on the distorted mean image based on the correction factor image to obtain a corrected image; the judgment module is configured to calculate the variance of the corrected image and the variance of the distorted mean image respectively, and judge whether the variance of the corrected image is less than the variance of the distorted mean image; the recording module is configured to, if the variance of the corrected image is less than the variance of the distorted mean image, record the variance of the corrected image of this filtering, and perform filtering and non-uniformity correction of the radiation response on the corrected image again until the variance of the corrected image is not less than the variance of the distorted mean image or the variance of the corrected image before this filtering; the determination module is configured to use the correction factor image corresponding to the minimum variance of the recorded corrected image as the effective calibration parameter for the non-uniformity of the radiation response of the to-be-calibrated area array camera.

9. An electronic device, characterized in that, Including: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the computer program, the method described in any one of claims 1-7 is implemented.

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

Images