Aerial moving target detection method based on low-temperature shielding

Abstract

The invention discloses an aerial moving target detection method based on low-temperature shielding, and the method comprises the following steps: (1) obtaining target image data observed by continuous frames and camera parameters, carrying out the preliminary judgment of a target based on a frame difference method at a fixed frame interval, obtaining a sub-pixel target position, and extracting a target region of interest; (2) according to the obtained sub-pixel target position and the extracted target region of interest, using a proportional deduction method to remove the image background gray scale, and extracting the actual energy value of the low-temperature shielding target; and (3) a speed curve is fitted through camera parameters and the position of a target center pixel, a parameter combination model of a target speed, scale and energy change curve based on a multi-frame data sequence is constructed, and target detection is completed. According to the invention, the aircraft target in the low-temperature shielding state can be effectively detected, and the detection efficiency is improved.

Description

Technical Field

[0001] The invention belongs to the field of target detection, and in particular relates to a method for detecting aerial moving targets based on low-temperature shielding. Background Art

[0002] Target detection and tracking of aircraft is a hot topic and difficulty in the current research of infrared detection technology. Stealth aircraft greatly reduces its detectability in radar and infrared detectors by using special materials, coatings and aerodynamic designs. Especially in low-temperature environments, its infrared radiation characteristics are further weakened, which brings great challenges to detection work.

[0003] Traditional space-based infrared target detection methods mainly rely on the tail flame formed by the target when accelerating and the surface and surrounding air temperature rise caused by the friction between the skin and the air during high-speed flight. Threshold segmentation is used to detect high-energy point targets from the low-temperature background. The mean value of the background pixels around the point target is subtracted to extract the point target energy.

[0004] For example, a Chinese patent document with publication number CN104199045A discloses a method and device for detecting high-speed aircraft in the air. The method detects the high-speed aircraft by measuring the spontaneous Rayleigh-Brillouin scattering spectrum of the tail flame of the high-speed aircraft in the air. The presence of a Brillouin scattering peak in the spontaneous Rayleigh-Brillouin scattering spectrum 180° backward in the atmosphere is used to determine whether there is a high-speed aircraft in the air, and the position information of the high-speed aircraft can be measured.

[0005] A Chinese patent document with publication number CN105243289A discloses an integrated modeling method for the infrared radiation characteristics of complex targets. The spectral ray tracing method is used throughout the entire solution process, and a solution model suitable for ray tracing is established. The method is suitable for simulating the infrared radiation characteristics of complex target aircraft including tail flames under specific flight conditions.

[0006] In actual work, the relationship between the aircraft skin and the background brightness is variable depending on its material, speed, background environment, etc. When the aircraft is flying steadily, its skin temperature is lower than the background environment, and it appears as a low-response point target in the long-wave infrared spectrum, which means that it has a low-temperature shielding effect on the background.

[0007] Therefore, in view of this characteristic, a new target detection method needs to be designed to complete the detection and energy extraction of targets under low-temperature shielding conditions, so as to effectively identify aircraft in different flight states. Summary of the invention

[0008] In order to overcome the shortcomings of existing detection methods, the present invention provides an aerial moving target detection method based on low-temperature shielding, which can effectively detect aircraft targets in a low-temperature shielding state and improve detection efficiency.

[0009] A method for detecting aerial moving targets based on low temperature shielding comprises the following steps:

[0010] (1) Obtain target image data and camera parameters from continuous frame observations, perform preliminary target judgment based on the frame difference method at a fixed frame interval, obtain the sub-pixel target position, and extract the target region of interest;

[0011] (2) Based on the obtained sub-pixel target position and the extracted target region of interest, the image background grayscale is removed using the proportional subtraction method to extract the actual energy value of the low-temperature shielding target;

[0012] (3) The velocity curve is fitted by the camera parameters and the position of the target center pixel, and a parameter combination model of the target velocity, scale, and energy change curve based on the multi-frame data sequence is constructed to complete target detection.

[0013] The present invention performs sub-pixel level measurement of target position and size based on multi-frame image sequences and camera imaging parameters, extracts the target's true energy through sub-pixel level proportional segmentation of target and background energy, and achieves optimal detection within the flight cycle based on high-precision solution parameters.

[0014] The specific process of step (1) is as follows:

[0015] (1-1) Obtaining a target image observed in continuous frames, preprocessing the target image, correcting the image non-uniformity and removing blind pixels to smooth the image according to camera parameters, and converting the image into a grayscale image;

[0016] (1-2) Select a fixed frame interval according to the expected target speed parameter, use the frame difference method to obtain a differential image, and select the possible point target area, that is, the sub-pixel target position;

[0017] (1-3) Select a pixel area of ​​a certain size around each point target area and extract it as the target area of ​​interest.

[0018] In step (1-2), the formula for obtaining the differential image using the frame difference method is as follows:

[0019] D k (x,y)=|I k (x,y)-I k-t (x,y)|

[0020] Among them, D k is a differential image, and the grayscale value response of each point is determined by the k-th frame image I k With the kt-th frame image I k-t The difference is obtained, and t is a fixed frame interval.

[0021] The specific process of step (2) is as follows:

[0022] (2-1) according to the obtained sub-pixel target position and the extracted target region of interest, the center of mass of the cryogenically shielded point target is obtained by using the system optical point spread function obtained by imaging system testing or simulation through the least squares method;

[0023] (2-2) Based on the obtained two-dimensional function fitting result, the accurate target centroid position and the fitted energy distribution function, the energy distribution function is normalized to obtain the energy distribution ratio of each pixel of the target point;

[0024] (2-3) The grayscale mean of the edge area in the target region of interest is used as the background grayscale, and background subtraction is performed according to the energy distribution ratio of each pixel. The results are summed to obtain the actual energy of the low-temperature shielding target.

[0025] In step (2-1), a Gaussian function is used as the point spread function of the overall system for target extraction.

[0026] The centroid of the low-temperature shielding point target is obtained by the least squares method, and the formula is as follows:

[0027]

[0028] In the formula, P′ i,j is the grayscale value of the actual pixel, B′ is the background estimation value, I′ is the target energy intensity to be determined, (x′ c ,y′ c ) is the center of mass position of the target to be determined, (x i,j ,y i,j ) are the coordinates of each point in the region of interest.

[0029] In step (2-3), the actual energy of the low-temperature shielding target is obtained, and the calculation formula is as follows:

[0030]

[0031] Where m and n are the sizes of the region of interest, DN i.j is the actual grayscale response of the pixel to be processed, is the grayscale response mean of the background pixels, ePSF is the point spread function of the fitted system, L is the target energy value expressed in grayscale, (x′ c ,y′ c ) is the obtained sub-pixel target centroid position, (x i,j ,y i,j ) are the coordinates of each point in the pixel energy distribution area.

[0032] In step (3), for multiple frames of data, the speed between adjacent frames is calculated as follows:

[0033]

[0034] Among them, v i represents the speed between the i-th frames, i≥2; (x i ,y i ) is the sub-pixel centroid position of the target in the current frame, (x i-1 ,t i-1 ) is the sub-pixel centroid position of the target in the previous frame. Based on the above formula and the centroid position result of (2-1) and the actual energy result of (2-3), a parameter combination model of the low-temperature shielding target in a multi-frame sequence can be formed. Its single-frame parameters include speed, scale and energy information, as shown below:

[0035] F(i)={x i ,y i ,v i ; ,d i ,L i}

[0036] In the formula, (x i ,y i ,) represents the center of mass position of the target in the current frame, v i Indicates the current frame target speed, d i Indicates the target size, L i Represents the target energy.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. The present invention adopts a low-temperature shielding image sequence template instead of the traditional high-energy threshold template, which can effectively detect aircraft targets in a low-temperature shielding state and improve the detection efficiency;

[0039] 2. The present invention adopts a sub-pixel level background ratio subtraction method to replace the original background pixel mean subtraction method to obtain the low-temperature shielding target energy, solving the problem that the commonly used method cannot effectively extract the low-temperature target energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of a method for detecting aerial moving targets based on low temperature shielding according to an embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram of a low-temperature shielding target initially obtained in an embodiment of the present invention;

[0042] Figure 3 The graph is a plot of the response values ​​of the actual low-temperature shielding target. DETAILED DESCRIPTION

[0043] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be pointed out that the embodiments described below are intended to facilitate the understanding of the present invention and do not have any limiting effect on the present invention.

[0044] like Figure 1 As shown, a method for detecting aerial moving targets based on low temperature shielding includes the following steps:

[0045] S1, obtain the target image data of continuous frame observation and the imaging parameters of the camera, and make a preliminary judgment of the target based on the frame difference method at a fixed frame interval. The specific steps are as follows:

[0046] S101, pre-process the target image, perform image non-uniformity correction and blind pixel removal according to relevant parameters to make the image smooth, and convert the image into a grayscale image. Select a fixed frame interval according to the expected target speed parameter, and use the frame difference method to make a preliminary judgment on the target position, as shown in the following formula:

[0047] D k (x,y)=|I k (x,y)-I k-t (x,y)|

[0048] Among them, D k is a differential image, and the grayscale value response of each point is determined by the k-th frame image I k With the kt-th frame image I k-t For the differential image D k Perform threshold segmentation and select possible point target areas.

[0049] S102, in order to reduce the amount of subsequent calculations, a pixel area of ​​a certain size around each point target area is selected as the region of interest for extraction, and subsequent centroid extraction and scale extraction operations are performed. The size of the area is determined by the system's computing power and the expected size of the target.

[0050] In the embodiment of the present invention, an image of a low-temperature shielded target is used, and the target is extracted using a frame difference of 1 frame. After the target is found, 11×11 pixels around the target are initially measured and extracted as the region of interest. Figure 2 This is the initial acquisition of the low-temperature shielding target.

[0051] S2, based on multi-frame data and sub-pixel centroid positioning method, obtain the image plane position and sub-pixel scale of the target, use the proportional subtraction method to remove the image background grayscale, and extract the target energy value.

[0052] S201, based on the sub-pixel target position obtained by the frame difference method and the extracted target region of interest, the system optical point spread function obtained by imaging system testing or simulation is used to obtain the centroid of the low-temperature shielding point target by the least square method, and its expression is as follows:

[0053]

[0054] In the example shown in step S1, a Gaussian function is used as the point spread function of the overall system to extract the target, and the energy distribution of the target along the x-axis direction is as follows: Figure 3 As shown, the Gaussian function model used for energy extraction can be expressed as:

[0055]

[0056] Among them, x0, y0 are the centroid positions of the target, and a is the intensity coefficient of the target. The sub-pixel centroid position of the target obtained by fitting on the original image is (517.5, 487.5).

[0057] S202, based on the obtained two-dimensional function fitting result, the accurate target centroid position and the fitted energy distribution function, the energy distribution function is normalized to obtain the energy distribution ratio of each pixel of the target point.

[0058] In the example shown in step S1, the energy distribution ratio of each pixel of the target point is shown in the following Table 1. The value of each point is the target energy ratio according to the fitting result.

[0059] Table 1

[0060] 0.0114 0.1793 0.1845 0.0176 0.2076 0.6818 0.6964 0.2251 0.2049 0.6747 0.6892 0.2222 0.0085 0.1719 0.1769 0.0145

[0061] S203, using the grayscale mean of the edge area of ​​the region of interest as the background grayscale, performing background subtraction according to the energy distribution ratio of each pixel, and summing the results to obtain the actual energy of the low-temperature shielding target. This calculation method is described as follows:

[0062]

[0063] Among them, m and n are the sizes of the region of interest, DN i.j is the actual grayscale response of the pixel to be processed, is the mean grayscale response of the background pixels, ePSF is the point spread function of the system actually fitted, and L is the target energy value expressed in grayscale. The target energy information can be obtained based on this value and the radiation calibration result of the system.

[0064] In the example shown in step S1, the background grayscale average is 2310. For the target area, the actual energy corresponding grayscale value calculated by this method is L=9841.5. The target energy information can be obtained based on this value and the radiation calibration result of the system.

[0065] S3, by fitting the velocity curve through the camera parameters and the position of the target center pixel, a parameter combination model of the target velocity, scale, and energy change curve based on the multi-frame data sequence is constructed.

[0066] For multi-frame data, the speed between adjacent frames is calculated as follows:

[0067]

[0068] Among them, v i represents the speed between the i-th frames (i≥2), (x i ,y i ) is the sub-pixel centroid position of the target in the current frame, (x i-1 ,y i-1 ) is the sub-pixel centroid position of the target in the previous frame. Based on the above formula, the centroid position result and the actual energy result, a parameter combination model of the low-temperature shielding target in a multi-frame sequence can be formed. Its single-frame parameters include speed, scale and energy information, as shown below.

[0069] F(i)={x i ,y i ,v i ,d i ,L i}

[0070] In the formula, (x i ,y i ,) represents the center of mass position of the target in the current frame, v i Indicates the current frame target speed, d i Indicates the target size, L i Represents the target energy.

[0071] The embodiments described above provide a detailed description of the technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, supplements and equivalent substitutions made within the scope of the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for detecting aerial moving targets based on low temperature shielding, characterized in that: The following steps are involved: (1) Obtain target image data and camera parameters from continuous frame observations, perform preliminary target judgment based on the frame difference method at a fixed frame interval, obtain the sub-pixel target position, and extract the target region of interest; (2) Based on the obtained sub-pixel target position and the extracted target region of interest, the image background grayscale is removed using the proportional subtraction method to extract the actual energy value of the low-temperature shielding target; (3) The velocity curve is fitted by the camera parameters and the position of the target center pixel, and a parameter combination model of the target velocity, scale, and energy change curve based on the multi-frame data sequence is constructed to complete target detection.

2. The method for detecting aerial moving targets based on low temperature shielding according to claim 1 is characterized in that: The specific process of step (1) is as follows: (1-1) Obtaining a target image observed in continuous frames, preprocessing the target image, correcting the image non-uniformity and removing blind pixels to smooth the image according to camera parameters, and converting the image into a grayscale image; (1-2) Select a fixed frame interval according to the expected target speed parameter, use the frame difference method to obtain a differential image, and select the possible point target area, that is, the sub-pixel target position; (1-3) Select a pixel area of ​​a certain size around each point target area and extract it as the target area of ​​interest.

3. The method for detecting aerial moving targets based on low temperature shielding according to claim 2 is characterized in that: In step (1-2), the formula for obtaining the differential image using the frame difference method is as follows: D k (x,y)=|I k (x,y)-I k-t (x,y)| Among them, D k is a differential image, and the grayscale value response of each point is determined by the k-th frame image I k With the kt-th frame image I k-t The difference is obtained, and t is a fixed frame interval.

4. The method for detecting aerial moving targets based on low temperature shielding according to claim 1, characterized in that: The specific process of step (2) is as follows: (2-1) according to the obtained sub-pixel target position and the extracted target region of interest, the center of mass of the cryogenically shielded point target is obtained by using the system optical point spread function obtained by imaging system testing or simulation through the least squares method; (2-2) Based on the obtained two-dimensional diffusion function fitting result, the accurate target centroid position and the fitted energy distribution function, the energy distribution function is normalized to obtain the energy distribution ratio of each pixel of the target point; (2-3) The grayscale mean of the edge area in the target region of interest is used as the background grayscale, and background subtraction is performed according to the energy distribution ratio of each pixel. The results are summed to obtain the actual energy of the low-temperature shielding target.

5. The method for detecting aerial moving targets based on low temperature shielding according to claim 4 is characterized in that: In step (2-1), a Gaussian function is used as the point spread function of the overall system for target extraction.

6. The method for detecting aerial moving targets based on low temperature shielding according to claim 4 is characterized in that: In step (2-1), the centroid of the low-temperature shielding point target is obtained by the least squares method, and the formula is as follows: In the formula, P′ i,j is the grayscale value of the actual pixel, B′ is the background estimation value, I′ is the target energy intensity to be determined, (x′ c ,y′ c ) is the centroid position of the sub-pixel target to be determined, (x i,j ,y i,j ) are the coordinates of each point in the region of interest.

7. The method for detecting aerial moving targets based on low temperature shielding according to claim 4, characterized in that: In step (2-3), the actual energy of the low-temperature shielding target is obtained, and the calculation formula is as follows: Where m and n are the sizes of the region of interest, DN i.j is the actual grayscale response of the pixel to be processed, is the grayscale response mean of the background pixels, ePSF is the point spread function of the fitted system, L is the target energy value expressed in grayscale, (x′ c ,y′ c ) is the obtained sub-pixel target centroid position, (x i,j ,y i,j ) are the coordinates of each point in the region of interest.

8. The method for detecting aerial moving targets based on low temperature shielding according to claim 4 is characterized in that: In step (3), for multiple frames of data, the speed between adjacent frames is calculated as follows: Among them, v i represents the speed between the i-th frames, i≥2; (x i ,y i ) is the sub-pixel centroid position of the target in the current frame, (x i-1 ,y i-1 ) is the sub-pixel centroid position of the target in the previous frame. Based on the above formula and the centroid position result of (2-1) and the actual energy result of (2-3), a parameter combination model of the low-temperature shielding target in a multi-frame sequence is formed. Its single-frame parameters include speed, scale and energy information, as shown below: F(i)={x i ,y i ,v i ,d i ,L i } In the formula, (x i ,y i ,) represents the center of mass position of the target in the current frame, v i Indicates the current frame target speed, d i Indicates the target size, L i Represents the target energy.

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