Image gain non-uniformity correction method and device for scanning infrared detector

Abstract

The present invention provides a method and device for correcting image gain non-uniformity of a scanning infrared detector, which can improve the accuracy of image non-uniformity correction. The method includes: determining the first detector output signal of the first frame image after correcting the bias non-uniformity, the second detector output signal of the second frame image, and the inter-frame motion translation, the first frame image and the second frame image are any two adjacent frames of multiple frames of images after correcting the bias non-uniformity; constructing a gain difference matrix according to the first detector output signal, the registration detector output signal, and the inter-frame motion translation; transforming and multiplying the gain difference matrix to obtain a gain correction matrix; calculating the average value of the gain correction matrix row by row to obtain a gain correction vector, and adding the gain correction vector to a first-in-first-out queue; calculating the average vector of multiple gain correction vectors in the first-in-first-out queue; correcting the input image according to the average vector and the pixel value of the input image.

Description

Technical Field

[0001] The present invention relates to the field of infrared image processing technology, and in particular to a method and device for correcting image gain non-uniformity of a scanning infrared detector. Background Art

[0002] The scanning infrared detector is a series of strip-shaped infrared focal planes that are pushed horizontally, and then these columns are stitched together to form an infrared image. Like all infrared focal planes, scanning focal planes also have non-uniform response problems. Due to the use of push-broom imaging, the non-uniformity of the scanning infrared detector is ultimately manifested in the infrared image as a significant stripe-shaped fixed pattern noise along the push-broom direction.

[0003] It is a mature technical means to achieve non-uniformity correction through calibration technology. The infrared camera is allowed to shoot black bodies of different temperatures to obtain scene radiation with uniform temperature in space within the camera's field of view. Then, linear or high-order fitting methods are used to obtain gain and bias parameters to compensate for the non-uniformity. However, the spatial non-uniformity response of the focal plane will drift slowly over time, and the correction parameters need to be continuously estimated and updated, otherwise fixed pattern noise will reappear in the output image frame. For calibration correction technology, this means that during the use of the infrared camera, a black body target needs to be frequently used to block the camera's field of view for calibration calculations, which may result in the omission of important scene information during the calibration process and cannot meet the needs of practical applications.

[0004] In order to overcome the shortcomings of the blackbody calibration method, the scene-based non-uniformity correction method dynamically estimates and removes non-uniformity based on the captured infrared image scene information. Traditional scene-based non-uniformity correction algorithms can be divided into three categories: The first method is based on constant statistics, assuming that the time domain mean and variance of each detector are identical, and requires that the captured scene radiation has sufficient diversity, which is difficult to fully meet in practical applications. The second method is based on neural networks, which requires the construction of a neural network and the training of the correction parameters of the neural network based on the input scene information. The calculation is large and the convergence is difficult. The third algorithm is based on image registration, which aligns the image scene that has undergone translational motion based on the inter-frame motion information, and then calculates the non-uniformity correction coefficient based on the difference in the signal response of the previous and next frames. Usually, it can only correct bias non-uniformity.

[0005] Therefore, how to better correct the non-uniformity of infrared images based on scene information is still a technical problem that needs to be solved urgently. Summary of the invention

[0006] The embodiment of the present invention provides a method and device for correcting image gain non-uniformity of a scanning infrared detector, which can improve the accuracy of image non-uniformity correction.

[0007] A first aspect of the present invention provides a method for correcting image gain non-uniformity of a scanning infrared detector, comprising:

[0008] Determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of a plurality of frames of images after bias non-uniformity correction;

[0009] Determine the registration detector output signal according to the second detector output signal and the inter-frame running translation;

[0010] constructing a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation;

[0011] Transforming and column-wise multiplying the gain difference matrix to obtain a gain correction matrix;

[0012] Calculating the average value of the gain correction matrix row by row to obtain the gain correction vector, and adding the gain correction vector to a first-in-first-out queue;

[0013] Calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector;

[0014] The gain non-uniformity correction is performed on the input image according to the average gain correction vector and the pixel value of the input image, and the input image is an infrared image after the bias non-uniformity is corrected.

[0015] A second aspect of the present invention provides an image gain non-uniformity correction device for a scanning infrared detector, comprising:

[0016] A determination module, used to determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of multiple frames of images after bias non-uniformity correction;

[0017] The determination module is further used to determine the registration detector output signal according to the second detector output signal and the inter-frame running translation amount;

[0018] A construction module, configured to construct a gain difference matrix according to the output signal of the first detector, the output signal of the registration detector and the inter-frame motion translation;

[0019] A transformation and multiplication module, used for transforming and multiplying the gain difference matrix by columns to obtain a gain correction matrix;

[0020] A calculation and adding module, used for calculating the average value of the gain correction matrix row by row to obtain the gain correction vector, and adding the gain correction vector to a first-in-first-out queue;

[0021] A gain calculation module, used for calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector;

[0022] The correction module is used to perform gain non-uniformity correction on the input image according to the average gain correction vector and the pixel value of the input image, and the input image is an infrared image after the bias non-uniformity is corrected.

[0023] In a possible design, the determining module is specifically used for:

[0024] The output signal of the first detector is determined by the following formula:

[0025] y k (i,j)=g(i)φ k (i,j);

[0026] Among them, y k (i, j) is the output signal of the first detector, i = 1, 2, ..., M, j = 1, 2, ..., N, M × N is the resolution of the first frame image, φ k (i, j) is the actual infrared radiation value of the scene corresponding to the first frame image, and g(i) is the gain non-uniformity parameter.

[0027] In a possible design, the construction module is specifically used for:

[0028] The values ​​of each element in the gain difference matrix are determined by the following formula:

[0029]

[0030] Among them, D G (i, j) is the gain difference matrix D G The value at coordinate (i,j), y k (i, j) is the output signal of the first detector, y k-1 (i-α,j-β)=g * (i-α)φ k-1 (i-α, j-β) is the output signal of the registration detector, (α, β) is the inter-frame motion translation, is the integer part, Δβ is the decimal part;

[0031] y k-1 (i-α,j-β)=g* (i-α)φ k-1 (i-α,j-β)=[(1-α)g(i)+αg(i-1)]φ k (i,j);

[0032] or,

[0033]

[0034] Among them, g * (i-α) is the ideal gain coefficient after translation;

[0035] The gain difference matrix is ​​constructed based on the values ​​of each element in the gain difference matrix by the following formula:

[0036]

[0037] In a possible design, the transformation accumulation module is specifically used for:

[0038] The gain difference matrix is ​​transformed by the following formula to obtain a transformation matrix:

[0039]

[0040] in, is the transformation matrix;

[0041] The gain correction matrix is ​​obtained by multiplying the transformation matrix column by column using the following formula: The values ​​of each element:

[0042]

[0043] in, is the gain correction matrix The value of each element in, g(s) is the gain correction matrix The non-uniformity coefficient of the s-th row in .

[0044] In a possible design, the calculation adding module is specifically used for:

[0045] The gain correction vector is determined by the following formula:

[0046]

[0047] in, is the gain correction vector.

[0048] In a possible design, the gain calculation module is specifically used for:

[0049] The average gain correction vector is determined by the following formula

[0050]

[0051] in, is the average gain correction vector, L is the number of gain correction vectors currently stored in the FIFO queue, is the average value of L different gain correction coefficients.

[0052] In a possible design, the correction module is specifically used for:

[0053] The gain non-uniformity correction of the input image is performed by the following formula:

[0054]

[0055] Among them, x q (i, j) is the pixel value of the input image after gain non-uniformity correction, is the average gain correction vector, y q (i, j) is the detector output signal of the input image, is the average value of the L different gain correction coefficients, g(i) is the gain non-uniformity parameter, φ q (i, j) is the actual infrared radiation value of the scene corresponding to the input image.

[0056] The third aspect of the present invention provides an electronic device, comprising a memory and a processor, wherein the processor is used to implement the steps of the image gain non-uniformity correction method of the scanning infrared detector as described in the first aspect when executing the computer management program stored in the memory.

[0057] A fourth aspect of the present invention provides a computer-readable storage medium having a computer management program stored thereon, which, when executed by a processor, implements the steps of the image gain non-uniformity correction method for a scanning infrared detector as described in the first aspect above.

[0058] In summary, it can be seen that in the embodiment provided by the present invention, the gain difference matrix is ​​constructed by the difference of the infrared detector signal output by the same scene radiation in the previous and next frame images, and the average gain correction vector is obtained by further transforming and calculating the gain difference matrix, and all gain non-uniformities in the image are corrected to the same value, thereby achieving uniform image output. In this way, the gain non-uniformity problem ignored by the traditional registration-based infrared non-uniformity correction method can be solved, the residual gain non-uniformity can be further corrected, and the accuracy of image non-uniformity correction can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A schematic diagram of a flow chart of a method for correcting image gain non-uniformity of a scanning infrared detector provided by an embodiment of the present invention;

[0060] Figure 2 A virtual structural diagram of an image gain non-uniformity correction device for a scanning infrared detector provided by an embodiment of the present invention;

[0061] Figure 3 A schematic diagram of the hardware structure of the image gain non-uniformity correction device for a scanning infrared detector provided by an embodiment of the present invention;

[0062] Figure 4 A schematic diagram of an electronic device according to an embodiment of the present invention;

[0063] Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0065] In the following description, specific embodiments of the present invention will be described with reference to steps and symbols performed by one or more computers, unless otherwise stated. Therefore, these steps and operations will be mentioned several times as being performed by a computer, and computer execution referred to herein includes operations by a computer processing unit of electronic signals representing data in a structured form. This operation converts the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise change the operation of the computer in a manner familiar to testers in the field. The data structure maintained by the data is a physical location in the memory, which has specific characteristics defined by the data format. However, the principles of the present invention are described in the above text, which does not represent a limitation, and testers in the field will understand that the various steps and operations described below can also be implemented in hardware.

[0066] The principles of the present invention operate with many other general or special purpose computing, communication environments or configurations. Examples of well-known computing systems, environments and configurations suitable for use with the present invention may include, but are not limited to, handheld phones, personal computers, servers, multiprocessor systems, microcomputer-based systems, mainframe computers, and distributed computing environments, including any of the above systems or devices.

[0067] The terms "first", "second", and "third" in the present invention are used to distinguish different objects rather than to describe a specific order. In addition, the terms "include", "have", and any variations thereof are intended to cover non-exclusive inclusions.

[0068] The image gain non-uniformity correction method for the scanning infrared detector provided by the present invention is explained below from the perspective of the image gain non-uniformity correction device for the scanning infrared detector. The image gain non-uniformity correction device for the scanning infrared detector can be a server or a service unit in the server, without specific limitation.

[0069] See also Figure 1 , Figure 1 A schematic flow chart of a method for correcting image gain non-uniformity of a scanning infrared detector provided in an embodiment of the present invention, wherein the method for correcting image gain non-uniformity of a scanning infrared detector comprises:

[0070] 101. Determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation amount.

[0071] In this embodiment, assuming that the scanning direction of the detector is the horizontal direction of the output image, the same row of pixels in the output image are generated by the same one (group) of detectors, so the same row of pixels have the same gain non-uniformity coefficient. The image gain non-uniformity correction device of the scanning infrared detector can determine the first detector output signal of the first frame image after correcting the bias non-uniformity, the second detector output signal of the second frame image, and the inter-frame motion translation, wherein the first frame image and the second frame image are any adjacent front and rear frame images in the multi-frame image obtained after the bias non-uniformity is corrected by the scanning infrared detector non-uniformity correction method based on registration. The specific scanning infrared detector image gain non-uniformity correction device can determine the first detector output signal and the second detector output signal by the following formula:

[0072] y k (i,j)=g(i)φ k (i,j);

[0073] y k-1 (i,j)=g(i)φ k-1 (i,j);

[0074] Among them, y k (i,j) is the output signal of the first detector, y k-1 (i,j) is the output signal of the second detector, i.e., y k (i,j) is the first frame image Y kThe detector output signal of the pixel coordinate (i, j) in , i = 1, 2, ..., M, j = 1, 2, ..., N, M × N is the resolution of the first frame image, φ k (i, j) is the actual infrared radiation value of the scene corresponding to the first frame image, φ k-1 (i, j) is the real infrared radiation value of the scene corresponding to the second frame image, and g(i) is the gain non-uniformity parameter;

[0075] It should be noted that the inter-frame motion translation of the previous and next frame images is (α, β), that is, the translation (α, β) generated between the kth frame and the k-1th frame output by the detector. The horizontal translation β is decomposed into integer parts: and the fractional part Δβ, that is

[0076] In one embodiment, the translation of the target frame image perpendicular to the detector scanning direction is defined as a sub-pixel translation, that is, 0<|α|≤1; the translation β parallel to the detector scanning direction is not required to be sub-pixel, that is, |β| can be greater than 1, and continuous frames that do not meet the translation requirements can be discarded. For the convenience of description, it is assumed that the vertical translation satisfies 0≤α<1, that is, the scene is sub-pixel translated downward; the horizontal translation satisfies β≥0, that is, the scene is translated to the right. The cases of -1<α≤0 (the scene is sub-pixel translated upward) or β≤0 (the scene is translated to the left) are similar and will not be described in detail.

[0077] 102. Determine a registration detector output signal according to the second detector output signal and an inter-frame running translation amount.

[0078] In this embodiment, after determining the output signal of the second detector and the inter-frame motion parallelism, the image gain non-uniformity correction device of the scanning infrared detector can determine the output signal of the second detector according to the output signal of the second detector and the inter-frame motion translation. Since the output frame rate of the infrared imaging detector is high and the time interval between two consecutive frames is short, the change of the radiation value of each object in the scene of the image can be ignored. Then, the scene content at the coordinate (i, j) in the kth frame is the same as the scene content at the coordinate (i-α, j-β) in the k-1th frame, and has the same radiation value, that is, φ k (i,j)=φ k-1 (i-α,j-β).

[0079] It should be noted that since the radiation value in the scene cannot be measured directly, only the detector output, i.e. y k-1 (i-α,j-β)=g * (i-α)φ k-1 (i-α, j-β), where g * (i-α) is the ideal gain coefficient after translation.

[0080] In one embodiment, a linear interpolation model is used to calculate g * (i-α) is approximated, g * (i-α)=(1-α)g(i)+αg(i-1);

[0081] Then the output signal of the registration detector can be expressed by the following formula:

[0082] y k-1 (i-α,j-β)=g * (i-α)φ k-1 (i-α,j-β)=[(1-α)g(i)+αg(i-1)]φ k (i,j);

[0083] In one embodiment, y k-1 (i-α, j-β) is approximated using a bilinear interpolation model:

[0084]

[0085] Among them, g * (i-α) is the ideal gain coefficient after translation.

[0086] 103. Construct a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation.

[0087] In this embodiment, the image gain non-uniformity correction device of the scanning infrared detector determines the output signal y of the first detector. k (i, j), the registration detector output signal y k-1 After (i-α, j-β) and the inter-frame motion translation (α, β), the elements in the gain difference matrix can be calculated by the following formula, that is, the gain difference matrix D is calculated. G Values ​​within the valid numerical coordinate range in:

[0088]

[0089] Among them, D G (i,j) is the gain difference matrix D G The value at coordinate (i,j), y k (i,j) is the output signal of the first detector, y k-1 (i-α,j-β)=g * (i-α)φ k-1 (i-α, j-β) is the output signal of the registration detector, (α, β) is the inter-frame motion translation, is the integer part, Δβ is the decimal part;

[0090] Gain difference matrix D G The coordinate range of valid values ​​is the Y coordinates of the previous and next frames. k+1 With Y k The scene overlap area, that is, i = 2, 3, ..., M, For non-overlapping regions, The pixels whose values ​​do not satisfy the above formula are not included in the subsequent calculations. In addition, for i=1, let D G (1,j)=1, then the gain difference matrix D G The valid values ​​satisfy the following relationship:

[0091]

[0092] Then we get the gain difference matrix D G .

[0093] 104. Transform the gain difference matrix and perform column-wise multiplication to obtain a gain correction matrix.

[0094] In this embodiment, the gain correction matrix aims to transform the gain difference matrix so that the value of each element in the transformed matrix is ​​equal to the target frame image Y k The gain correction of the pixels in the corresponding row in is the gain coefficient of the sth row. Specifically, the image gain non-uniformity correction device of the scanning infrared detector can correct the gain difference matrix D G The matrix undergoes row-by-row transformation in elementary transformation, and the gain difference matrix D G The first row in the matrix is ​​swapped with the next row of the first row one by one until the elements of the original first row are moved to the sth row position, and then the elements of the first s-1 rows after the move are set to the inverse of the original values ​​to obtain the transformation matrix Transformation Matrix It is expressed by the following formula:

[0095]

[0096] And transform the matrix Perform column-wise multiplication to obtain the gain correction matrix The value of each element in Calculate using the following formula:

[0097]

[0098] but The elements of which are consistent with the target frame image Y k Multiply the pixel values ​​of the corresponding rows in the gain correction matrix The target frame image Yk The gain non-uniformity coefficients of all pixels in are corrected to the non-uniformity coefficient g(s) of the sth row, thereby achieving uniform output of the infrared image.

[0099] 105. Calculate the average value of the gain correction matrix row by row to obtain a gain correction vector, and add the gain correction vector to a first-in-first-out queue.

[0100] In this embodiment, the gain correction vector is obtained by The elements in are averaged by row. Specifically, the image gain non-uniformity correction device of the scanning infrared detector can determine the gain correction vector by the following formula:

[0101]

[0102] The image gain non-uniformity correction device of the scanning infrared detector can construct a first-in-first-out queue (FIFO) in advance to store the latest L gain correction vectors. Whenever a new continuous frame image that satisfies the vertical sub-pixel translation is generated, the calculated gain correction vector is queued into the FIFO, and at the same time, the earliest gain correction vector in the FIFO is dequeued, keeping the number of gain correction vectors in the FIFO unchanged at L.

[0103] 106. Calculate an average vector of multiple gain correction vectors currently stored in the first-in-first-out queue to obtain an average gain correction vector.

[0104] In this embodiment, every time a new gain correction vector is queued, the image gain non-uniformity correction device of the scanning infrared detector can calculate the average gain correction vector by the following formula:

[0105]

[0106] in, represents the average value of L different gain correction coefficients, the average gain correction vector Always dynamically updated With the target frame image Y k Each column of the multiplication according to the row subscript can correct the gain non-uniformity coefficient of each pixel to the same value. Thereby achieving uniform output of infrared images.

[0107] 107. Perform gain non-uniformity correction on the input image according to the average gain correction vector and the pixel value of the input image.

[0108] In this embodiment, the image gain non-uniformity correction device of the scanning infrared detector calculates the average gain correction vector and converts the average gain correction vector into With the input image Y p Each column of the multiplication according to the row subscript can correct the gain non-uniformity coefficient of each pixel to the same value. Thereby, uniform output of infrared images is achieved. Specifically, the image gain non-uniformity correction device of the scanning infrared detector can perform gain non-uniformity correction on the target frame image by the following formula:

[0109]

[0110] Among them, x q (i, j) is the pixel value of the input image after gain non-uniformity correction, is the average gain correction vector, y q (i,j) is the detector output signal of the input image, is the average value of L different gain correction coefficients, g(i) is the gain non-uniformity parameter, φ q (i, j) is the actual infrared radiation value of the scene corresponding to the input image.

[0111] In summary, it can be seen that in the embodiment provided by the present invention, the gain difference matrix is ​​constructed by the difference of the infrared detector signal output by the same scene radiation in the previous and next frame images, and the average gain correction vector is obtained by further transforming and calculating the gain difference matrix, and all gain non-uniformities in the image are corrected to the same value, thereby achieving uniform image output. In this way, the gain non-uniformity problem ignored by the traditional registration-based infrared non-uniformity correction method can be solved, the residual gain non-uniformity can be further corrected, and the accuracy of image non-uniformity correction can be improved.

[0112] The above describes the embodiment of the present invention from the perspective of the image gain non-uniformity correction method of the scanning infrared detector. The following describes the embodiment of the present invention from the perspective of the image gain non-uniformity correction device of the scanning infrared detector.

[0113] See also Figure 2 , a virtual structural diagram of an image gain non-uniformity correction device for a scanning infrared detector according to an embodiment of the present invention, wherein the image gain non-uniformity correction device 200 for a scanning infrared detector comprises:

[0114] A determination module 201 is used to determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of a plurality of frames of images after bias non-uniformity correction;

[0115] The determination module 201 is further used to determine the registration detector output signal according to the second detector output signal and the inter-frame running translation;

[0116] A construction module 202, configured to construct a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation;

[0117] The transformation and multiplication module 203 is used to transform and multiply the gain difference matrix by columns to obtain a gain correction matrix;

[0118] A calculation and adding module 204, configured to calculate the average value of the gain correction matrix row by row to obtain the gain correction vector, and add the gain correction vector to a first-in-first-out queue;

[0119] A gain calculation module 205, configured to calculate an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector;

[0120] The correction module 206 is used to perform gain non-uniformity correction on the input image according to the average gain correction vector and the pixel value of the input image, wherein the input image is an infrared image after the offset non-uniformity is corrected.

[0121] In a possible design, the determining module 201 is specifically used for:

[0122] The output signal of the first detector is determined by the following formula:

[0123] y k (i,j)=g(i)φ k (i,j);

[0124] Among them, y k (i, j) is the output signal of the first detector, i = 1, 2, ..., M, j = 1, 2, ..., N, M × N is the resolution of the first frame image, φ k (i, j) is the actual infrared radiation value of the scene corresponding to the first frame image, and g(i) is the gain non-uniformity parameter.

[0125] In a possible design, the construction module 202 is specifically used for:

[0126] The values ​​of each element in the gain difference matrix are determined by the following formula:

[0127]

[0128] Among them, D G (i, j) is the gain difference matrix D G The value at coordinate (i,j), yk (i, j) is the output signal of the first detector, y k-1 (i-α,j-β)=g * (i-α)φ k-1 (i-α, j-β) is the output signal of the registration detector, (α, β) is the inter-frame motion translation, is the integer part, Δβ is the decimal part;

[0129] y k-1 (i-α,j-β)=g * (i-α)φ k-1 (i-α,j-β)=[(1-α)g(i)+αg(i-1)]φ k (i,j);

[0130] or,

[0131]

[0132] Among them, g * (i-α) is the ideal gain coefficient after translation;

[0133] The gain difference matrix is ​​constructed based on the values ​​of each element in the gain difference matrix by the following formula:

[0134]

[0135] In a possible design, the transformation accumulation module 203 is specifically used for:

[0136] The gain difference matrix is ​​transformed by the following formula to obtain a transformation matrix:

[0137]

[0138] in, is the transformation matrix;

[0139] The gain correction matrix is ​​obtained by multiplying the transformation matrix column by column using the following formula: The values ​​of each element:

[0140]

[0141] in, is the gain correction matrix The value of each element in, g(s) is the gain correction matrix The non-uniformity coefficient of the sth row in .

[0142] In a possible design, the calculation adding module 204 is specifically used for:

[0143] The gain correction vector is determined by the following formula:

[0144]

[0145] in, is the gain correction vector.

[0146] In a possible design, the gain calculation module 205 is specifically used for:

[0147] The average gain correction vector is determined by the following formula

[0148]

[0149] in, is the average gain correction vector, L is the number of gain correction vectors currently stored in the FIFO queue, is the average value of L different gain correction coefficients.

[0150] In a possible design, the correction module 206 is specifically used for:

[0151] The gain non-uniformity correction of the input image is performed by the following formula:

[0152]

[0153] Among them, x q (i, j) is the pixel value of the input image after gain non-uniformity correction, is the average gain correction vector, y q (i, j) is the detector output signal of the input image, is the average value of the L different gain correction coefficients, g(i) is the gain non-uniformity parameter, φ q (i, j) is the actual infrared radiation value of the scene corresponding to the input image.

[0154] above Figure 3 The image gain non-uniformity correction device of the scanning infrared detector in the embodiment of the present invention is described from the perspective of modular functional entities. The image gain non-uniformity correction device of the scanning infrared detector in the embodiment of the present invention is described in detail from the perspective of hardware processing. Please refer to FIG. 300, which is a schematic diagram of an embodiment of the image gain non-uniformity correction device 300 of the scanning infrared detector in the embodiment of the present invention. The image gain non-uniformity correction device 300 of the scanning infrared detector includes:

[0155] An input device 301, an output device 302, a processor 303 and a memory 304 (the number of the processor 303 can be one or more, Figure 3 In some embodiments of the present invention, the input device 301, the output device 302, the processor 303 and the memory 304 may be connected via a communication bus or other means, wherein: Figure 3 The communication bus connection is taken as an example.

[0156] Wherein, by calling the operation instruction stored in the memory 304, the processor 303 is used to perform the following steps:

[0157] Determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of a plurality of frames of images after bias non-uniformity correction;

[0158] Determine the registration detector output signal according to the second detector output signal and the inter-frame running translation;

[0159] constructing a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation;

[0160] Transforming and column-wise multiplying the gain difference matrix to obtain a gain correction matrix;

[0161] Calculating the average value of the gain correction matrix row by row to obtain the gain correction vector, and adding the gain correction vector to a first-in-first-out queue;

[0162] Calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector;

[0163] The gain non-uniformity correction is performed on the input image according to the average gain correction vector and the pixel value of the input image, and the input image is an infrared image after the bias non-uniformity is corrected.

[0164] By calling the operation instructions stored in the memory 304, the processor 303 is also used to execute Figure 1 Any method in the corresponding embodiment.

[0165] See also Figure 4 , Figure 4 A schematic diagram of an electronic device according to an embodiment of the present invention.

[0166] like Figure 4As shown, an embodiment of the present invention provides an electronic device, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0167] Determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of a plurality of frames of images after bias non-uniformity correction;

[0168] Determine the registration detector output signal according to the second detector output signal and the inter-frame running translation;

[0169] constructing a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation;

[0170] Transforming and column-wise multiplying the gain difference matrix to obtain a gain correction matrix;

[0171] Calculating the average value of the gain correction matrix row by row to obtain the gain correction vector, and adding the gain correction vector to a first-in-first-out queue;

[0172] Calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector;

[0173] The gain non-uniformity correction is performed on the input image according to the average gain correction vector and the pixel value of the input image, and the input image is an infrared image after the bias non-uniformity is corrected.

[0174] In the specific implementation process, when the processor 420 executes the computer program 411, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0175] Since the electronic device introduced in this embodiment is a device used to implement an image gain non-uniformity correction device of a scanning infrared detector in an embodiment of the present invention, based on the method introduced in the embodiment of the present invention, technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present invention will not be described in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of the present invention falls within the scope of protection of the present invention.

[0176] Please refer to Figure 500, which is a schematic diagram of an embodiment of a computer-readable storage medium provided by an embodiment of the present invention.

[0177] As shown in Figure 500, an embodiment of the present invention further provides a computer-readable storage medium 500, on which a computer program 511 is stored. When the computer program 511 is executed by a processor, the following steps are implemented:

[0178] Determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of a plurality of frames of images after bias non-uniformity correction;

[0179] Determine the registration detector output signal according to the second detector output signal and the inter-frame running translation;

[0180] constructing a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation;

[0181] Transforming and column-wise multiplying the gain difference matrix to obtain a gain correction matrix;

[0182] Calculating the average value of the gain correction matrix row by row to obtain the gain correction vector, and adding the gain correction vector to a first-in-first-out queue;

[0183] Calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector;

[0184] The gain non-uniformity correction is performed on the input image according to the average gain correction vector and the pixel value of the input image, and the input image is an infrared image after the bias non-uniformity is corrected.

[0185] In the specific implementation process, the computer program 511 is executed by the processor to achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0186] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0187] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0188] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0189] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0190] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0191] The embodiment of the present invention also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the following Figure 1 The process in the corresponding embodiment.

[0192] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and 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 may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may 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 may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0193] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0194] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices 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 are other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0195] 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.

[0196] 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. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0197] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment 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, etc., various media that can store program codes.

[0198] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A gain non-uniformity correction method for infrared images, characterized in that: include: Determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of a plurality of frames of images after bias non-uniformity correction; Determine the registration detector output signal according to the second detector output signal and the inter-frame running translation; constructing a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation; Transforming and column-wise multiplying the gain difference matrix to obtain a gain correction matrix; Calculating the average value of the gain correction matrix row by row to obtain a gain correction vector, and adding the gain correction vector to a first-in-first-out queue; Calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector; The gain non-uniformity correction is performed on the input image according to the average gain correction vector and the pixel value of the input image, and the input image is an infrared image after the bias non-uniformity is corrected.

2. The method according to claim 1, characterized in that The determining of the first detector output signal of the first frame image after the bias non-uniformity correction comprises: The output signal of the first detector is determined by the following formula: y k (i,j)=g(i)φ k (i,j); Among them, y k (i, j) is the output signal of the first detector, i = 1, 2, ..., M, j = 1, 2, ..., N, M × N is the resolution of the first frame image, φ k (i, j) is the actual infrared radiation value of the scene corresponding to the first frame image, and g(i) is the gain non-uniformity parameter.

3. The method according to claim 1, characterized in that The step of constructing a gain difference matrix according to the first detector output signal, the registration detector output signal and the inter-frame motion translation comprises: The values ​​of each element in the gain difference matrix are determined by the following formula: Among them, D G (i, j) is the gain difference matrix D G The value at coordinate (i,j), y k (i, j) is the output signal of the first detector, y k-1 (i-α,j-β)=g * (i-α)φ k-1 (i-α, j-β) is the output signal of the registration detector, (α, β) is the inter-frame motion translation, is the integer part, Δβ is the decimal part; y k-1 (i-α,j-β)=g * (i-a)φ k-1 (i-α,j-β)=[(1-α)g(i)+αg(i-1)]φ k (i,j); or, Among them, g * (i-α) is the ideal gain coefficient after translation; The gain difference matrix is ​​constructed based on the values ​​of each element in the gain difference matrix by the following formula:

4. The method according to claim 1, characterized in that: The step of transforming the gain difference matrix and multiplying the matrix by columns to obtain a gain correction matrix includes: The gain difference matrix is ​​transformed by the following formula to obtain a transformation matrix: in, is the transformation matrix; The gain correction matrix is ​​obtained by multiplying the transformation matrix column by column using the following formula: The values ​​of each element: in, is the gain correction matrix The value of each element in, g(s) is the gain correction matrix The non-uniformity coefficient of the s-th row in .

5. The method according to claim 1, characterized in that The step of calculating the average value of the gain correction matrix row by row to obtain the gain correction vector comprises: The gain correction vector is determined by the following formula: in, is the gain correction vector.

6. The method according to claim 1, characterized in that The step of calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector comprises: The average gain correction vector is determined by the following formula in, is the average gain correction vector, L is the number of gain correction vectors currently stored in the FIFO queue, is the average value of L different gain correction coefficients.

7. The method according to claim 1, characterized in that The performing gain non-uniformity correction on the input image according to the average gain correction vector and the pixel value of the input image comprises: The gain non-uniformity correction of the input image is performed by the following formula: Among them, x q (i, j) is the pixel value of the input image after gain non-uniformity correction, is the average gain correction vector, y q (i, j) is the detector output signal of the input image, is the average value of L different gain correction coefficients, g(i) is the gain non-uniformity parameter, φ q (i, j) is the actual infrared radiation value of the scene corresponding to the input image.

8. A gain non-uniformity correction device for infrared images, characterized in that: include: A determination module, used to determine a first detector output signal of a first frame image after bias non-uniformity correction, a second detector output signal of a second frame image, and an inter-frame motion translation, wherein the first frame image and the second frame image are any two adjacent frames of multiple frames of images after bias non-uniformity correction; The determination module is further used to determine the registration detector output signal according to the second detector output signal and the inter-frame running translation amount; A construction module, configured to construct a gain difference matrix according to the output signal of the first detector, the output signal of the registration detector and the inter-frame motion translation; A transformation and multiplication module, used for transforming and multiplying the gain difference matrix by columns to obtain a gain correction matrix; A calculation and adding module, used for calculating the average value of the gain correction matrix row by row to obtain a gain correction vector, and adding the gain correction vector to a first-in-first-out queue; A gain calculation module, used for calculating an average vector of a plurality of gain correction vectors currently stored in the FIFO queue to obtain an average gain correction vector; The correction module is used to perform gain non-uniformity correction on the input image according to the average gain correction vector and the pixel value of the input image, and the input image is an infrared image after the bias non-uniformity is corrected.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is used to implement the gain non-uniformity correction method for infrared images as described in any one of claims 1 to 7 when executing a computer management program stored in the memory.

10. A computer-readable storage medium having a computer management program stored thereon, characterized in that: When the computer management program is executed by a processor, the gain non-uniformity correction method for infrared images as claimed in any one of claims 1 to 7 is implemented.

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