CN111401195B - Sea surface target detection method based on multiband infrared image - Google Patents
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Abstract
A sea surface target detection method based on multiband infrared images belongs to the field of infrared target detection. The method is used for completing target detection based on infrared multiband image information aiming at the acquired infrared radiation images of the same scene in four different wave band ranges. Firstly, performing background estimation based on multiband vector characteristics; then, based on the multiband vector characteristic difference of the target and the background, calculating the vector distance and the vector included angle estimated by each pixel in the target scene and the background, and increasing the difference between the target and the background to further complete the background inhibition; and finally, dividing the target by adopting an adaptive threshold method. The method has the advantages that the signal-to-noise ratio of the target image is greatly improved by utilizing the multiband vector characteristic difference of the target and the background, the performance of the method is independent of the size, shape or motion information of the target, the method has strong adaptability, the implementation is easy, and the method can be applied to target detection and tracking under the complex sea surface background.
Description
Technical Field
The invention relates to a sea surface target detection method based on multiband infrared images, in particular to a complex sea clutter multiband target detection method based on background suppression, and belongs to the field of infrared target detection.
Background
The infrared target detection under the complex background is a core technology and key problem of an infrared imaging guidance system, and is one of hot spots for research of students at home and abroad in recent years. For the sea surface infrared target image, due to heat exchange between the target and the surrounding environment, and the scattering and absorption effects of air on heat radiation, the interference of a target signal on the sea wave background is large, so that the contrast ratio of the target and the background in the infrared image is poor, and the edge of the target is blurred, which brings great difficulty to the detection of the infrared target.
Aiming at infrared weak and small target detection in a complex environment, the infrared imaging detection mode of a single wave band faces a plurality of bottlenecks. Therefore, infrared imaging detection gradually develops towards multi-dimensional imaging directions such as dual-band imaging, multi-spectrum imaging and the like, and can provide richer multi-band or multi-spectrum imaging besides common two-dimensional intensity image information, so that better information input conditions are created for detection and identification of targets. But for the acquired multi-dimensional image information, how to effectively use and rapidly and accurately extract the target information is a key for improving the performance of the weapon system.
Disclosure of Invention
The invention aims to solve the technical problems that: the sea surface target detection method aims at the obtained infrared radiation images of the same scene in four different wave band ranges, and the target detection based on infrared multiband image information is completed. Firstly, performing background estimation based on multiband vector characteristics; then, based on the multiband vector characteristic difference of the target and the background, calculating the vector distance and the vector included angle estimated by each pixel in the target scene and the background, and increasing the difference between the target and the background to further complete the background inhibition; and finally, dividing the target by adopting an adaptive threshold method. The method has the advantages that the signal-to-noise ratio of the target image is greatly improved by utilizing the multiband vector characteristic difference of the target and the background, the performance of the method is independent of the size, shape or motion information of the target, the method has strong adaptability, the implementation is easy, and the method can be applied to target detection and tracking under the complex sea surface background.
The invention aims at realizing the following technical scheme:
a sea surface target detection method based on multiband infrared images comprises the following steps:
step one, collecting infrared images of a plurality of wave bands of the same target scene;
secondly, carrying out background estimation on the collected infrared images of a plurality of wave bands by utilizing the characteristic of the multiband vector to obtain a background estimation vector;
step three, calculating the distance and the included angle between the multiband feature vector of each pixel point in the target scene and the background estimation vector;
step four, synthesizing and calculating the distance and the included angle in the step three to obtain an image after background suppression;
and fifthly, dividing the image obtained in the step four by adopting a minimum error self-adaptive threshold method, and detecting a target position.
According to the sea surface target detection method based on the multiband infrared image, preferably, the infrared multiband imaging system based on rotary filtering is adopted to collect the target scene.
According to the sea surface target detection method based on the multiband infrared image, preferably, infrared images of four wavebands of the same target scene are collected; the wavelengths of the four wave bands are respectively: 3.7 μm-4.8 μm, 3.0 μm-3.3 μm, 3.4 μm-4.1 μm, 4.4 μm-4.9 μm.
In the sea surface target detection method based on the multiband infrared image, preferably, the frame frequency of each band of the infrared multiband imaging system based on the rotary filtering is not lower than 80Hz.
In the above sea surface target detection method based on multiband infrared image, preferably, the background estimation vector obtaining method includes: the average value of the infrared image of each wave band is calculated first, and then all the average values form a vector which is used as a background estimation vector.
In the sea surface target detection method based on the multiband infrared image, preferably, the method for calculating the distance and the included angle between the multiband feature vector and the background estimation vector of each pixel point in the target scene comprises the following steps: firstly, calculating the gray scale of an infrared image of each wave band, and then forming a vector of the gray scale of the infrared image of each wave band as a multiband feature vector; and finally, calculating the distance and the included angle between the multiband characteristic vector and the background estimation vector.
In the sea surface target detection method based on the multiband infrared image, preferably, the combination of the distance and the included angle is calculated as the product of the distance and the included angle of the multiband feature vector and the background estimation vector.
According to the sea surface target detection method based on the multiband infrared image, preferably, the image obtained in the step four is segmented by adopting a minimum error self-adaptive threshold method, and then the centroid coordinates of the obtained target segmented area are calculated, so that the required target detection result is obtained.
Compared with the prior art, the invention has the following beneficial effects:
(1) Compared with the prior art for detecting the target based on the difference of infrared radiation intensity, the method and the device can effectively distinguish the target from the background by utilizing the multiband vector characteristic difference between the target and the background, and achieve the purposes of suppressing the background and improving the signal-to-noise ratio of the image;
(2) The existing method mostly uses multi-band image information by fusing or pseudo-color reproduction of a plurality of images, so that the information quantity of the images is increased to a certain extent, and the aim of inhibiting the background noise of the images cannot be achieved; according to the method, based on a plurality of images with different wave bands, the multiband vector distance and the included angle estimated by each pixel point and the background are calculated, and the difference between the target and the background is maximized through a specific synthesis method, so that the signal-to-noise ratio of the images is greatly improved, and the detection and the identification of the infrared target are facilitated;
(3) The method carries out target detection based on the multiband vector characteristic difference between the artificial target and the natural background, the multiband vector characteristic difference between the target and the background is determined by respective spectrum radiation curves, the detection effect is independent of the size, shape, radiation intensity and motion information of the target, and the method has strong adaptability;
(4) When the method is used for background suppression, the multi-band vector distance and included angle information between the target and the background are directly extracted, simple synthesis operation is realized, complex operations such as airspace window scanning or frequency domain transformation are not needed, and the method is easy to realize and good in instantaneity.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 (a) is an original input 3.7 μm-4.8 μm infrared image of an embodiment of the present invention;
FIG. 2 (b) is an original input 3.0 μm-3.3 μm infrared image of an embodiment of the present invention;
FIG. 2 (c) is an original input 3.4 μm-4.1 μm infrared image of an embodiment of the present invention;
FIG. 2 (d) is a raw input 4.4 μm-4.9 μm infrared image of an embodiment of the present invention;
FIG. 3 (a) is a distance image of the multiband feature vector and the background estimation vector of each pixel point of the target scene in FIG. 2;
FIG. 3 (b) is an image of the angles between the multi-band feature vector and the background estimation vector of each pixel point of the target scene in FIG. 2;
FIG. 4 is a background suppression image after the information synthesis of FIGS. 3 (a) and 3 (b);
FIG. 5 is the thresholded target image of FIG. 4;
FIG. 6 is a schematic diagram of results obtained by the method of the present embodiment under different sea surface scenarios; wherein:
a1, A2 and A3: the original infrared intensity images of different scenes are sequentially obtained;
b1, B2 and B3: sequentially multi-band feature vector distance images corresponding to A1, A2 and A3;
c1, C2 and C3: the images of the multi-band characteristic vector included angles corresponding to A1, A2 and A3 are sequentially shown;
d1, D2 and D3: the background suppression images after the information synthesis corresponding to A1, A2 and A3 are sequentially shown.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
A sea surface target detection method based on multiband infrared images comprises the following steps:
step one, acquiring infrared images of multiple wavebands of the same target scene by adopting an infrared multiband imaging system based on rotary filtering; in the example, four wave band infrared images of the same target scene are acquired; the wavelengths of the four wave bands are respectively: 3.7 μm-4.8 μm, 3.0 μm-3.3 μm, 3.4 μm-4.1 μm, 4.4 μm-4.9 μm; the frame frequency of each wave band is not lower than 80Hz, and the time difference of the acquired images of different wave bands is ignored.
Secondly, carrying out background estimation on the collected infrared images of a plurality of wave bands by utilizing the characteristic of the multiband vector to obtain a background estimation vector; the background estimation vector obtaining method comprises the following steps: the average value of the infrared image of each wave band is calculated first, and then all the average values form a vector which is used as a background estimation vector.
Step three, calculating the distance and the included angle between the multiband feature vector of each pixel point in the target scene and the background estimation vector; the specific method comprises the following steps: firstly, calculating the gray scale of an infrared image of each wave band, and then forming a vector of the gray scale of the infrared image of each wave band as a multiband feature vector; and finally, calculating the distance and the included angle between the multiband characteristic vector and the background estimation vector.
Step four, synthesizing and calculating the distance and the included angle in the step three to obtain an image after background suppression; the synthetic calculation method is the product of the distance and the included angle of the multiband characteristic vector and the background estimation vector.
And fifthly, segmenting the image obtained in the fourth step by adopting a minimum error self-adaptive threshold method, and then calculating centroid coordinates of the obtained target segmented region, namely detecting the target position.
Examples:
fig. 1 is a schematic block flow diagram of an embodiment of the present invention. Mainly comprises the following steps: the method comprises four steps of multiband infrared image input, background estimation based on multiband vector characteristics, background suppression based on vector distance and included angle and threshold segmentation.
The method comprises the following steps:
step 1, an infrared multiband imaging system based on rotary filtering is provided, by installing a rotary filter in a light path of a traditional infrared imaging system, the light transmission wave bands of the filter are respectively 3.7-4.8 mu m, 3.0-3.3 mu m, 3.4-4.1 mu m and 4.4-4.9 mu m, the system sequentially acquires different wave band images of a target scene, the frame frequency of each wave band can reach 80Hz, and the time errors of the images of the different wave bands are approximately ignored in the method. Namely, the acquired infrared images of the same scene with the wave bands of 3.7 mu m-4.8 mu m, 3.0 mu m-3.3 mu m, 3.4 mu m-4.1 mu m and 4.4 mu m-4.9 mu m are input, as shown in the figures 2 (a), 2 (b), 2 (c) and 2 (d) respectively.
And 2, performing background estimation based on multiband vector characteristics on the four acquired multiband infrared images.
The average values of the infrared images of the wave bands of 3.7 μm-4.8 μm, 3.0 μm-3.3 μm, 3.4 μm-4.1 μm and 4.4 μm-4.9 μm, respectively, namely the average values of the infrared images of FIG. 2 (a), FIG. 2 (b), FIG. 2 (c) and FIG. 2 (d), are calculated as u 1 、u 2 、u 3 、u 4 Then the background estimate based on the multiband behaviour is vector a, a= (u) 1 ，u 2 ，u 3 ，u 4 )。
For small target images, the vast majority of the area in the image is the background area, so vector a characterizes the multiband behavior of the background in the target scene.
And step 3, calculating the distance and the included angle between the multiband characteristic vector of each pixel point in the target scene and the background estimation vector.
Let the infrared image gray levels of four wave bands (i.e. 3.7 μm-4.8 μm, 3.0 μm-3.3 μm, 3.4 μm-4.1 μm, 4.4 μm-4.9 μm) of FIG. 2 (a), FIG. 2 (b), FIG. 2 (c) and FIG. 2 (d) be f respectively 1 (i,j)、f 2 (i,j)、f 3 (i,j)、f 4 (i, j), i, j being the coordinates of the pixels in the image. The multiband feature vector for each pixel location in the target scene is denoted B (i, j), B (i, j) = (f) 1 (i,j)，f 2 (i,j)，f 3 (i,j)，f 4 (i,j))。
The distances d (i, j) and the included angles alpha (i, j) between the multiband feature vector and the background estimation vector of each pixel point in the target scene are calculated according to the formula (1) and the formula (2), and the resulting images are shown in fig. 3 (a) and 3 (b).
The multiband characteristic vector difference of the artificial target and the sea surface background is determined by the spectrum radiation curve difference of the artificial target and the sea surface background, so that the vector distance d (i, j) and the included angle alpha (i, j) between the artificial target and the sea surface background represent the difference between the artificial target and the sea surface background from the angle of spectrum radiation difference, and can be used as the basis of subsequent background suppression.
Step 4, carrying out specific synthesis calculation on the vector distance and the vector included angle based on the multiband characteristics to obtain an image after background suppression, wherein the calculation is as follows
g(i,j)＝α(i,j)×d(i,j) (3)
Where g (i, j) is an image after background suppression, α (i, j) is a multiband vector angle image between each pixel point in the target scene and the background, and d (i, j) is a multiband vector distance image. d (i, j) and alpha (i, j) reflect the multiband characteristic difference of the target and the background, compared with the infrared intensity image, the signal-to-noise ratio of the sea surface background is improved to a certain extent, but the background noise component in the image is still more, and the nonlinear stretching based on the vector included angle is carried out on the multiband characteristic vector distance of the target and the background by adopting the synthesis method of the formula (3), so that the background suppression effect is further improved, as shown in fig. 4.
And 5, performing target segmentation on the image after the background suppression by using a minimum error method. The minimum error thresholding is derived based on Bayes minimum error classification criteria, assuming that the gray scale distribution of the ideal target and background obeys a mixed normal distribution. The method is less influenced by the relative sizes of the target and the background, and is a good threshold selection method for small target images. The segmentation threshold is selected as follows.
η(t)＝1-ω o (t)lnω o (t)-ω b (t)lnω b (t)+ω o (t)lnσ o (t)+ω b (t)lnσ b (t)
In the method, in the process of the invention,ω o (t) and ω b (t) represents the prior probabilities of the target and background at a threshold of t for the original gray scale image,and->Representing the respective variances. When eta (t) takes the minimum value, the optimal segmentation threshold t is obtained * ：L is the gray scale of the image. With the optimal segmentation threshold, the segmentation results obtained are shown in fig. 5. On the basis, the centroid coordinates of the obtained target segmentation areas are calculated, and the required target detection result can be obtained.
The schematic diagrams of the target detection results under different sea-air scenes by adopting the method in the embodiment are shown in fig. 6, the original infrared intensity image (3.7-4.8 μm), the vector distance image, the vector included angle image and the background inhibition image after information synthesis are sequentially shown from left to right in fig. 6, and as can be seen, the signal-to-noise ratio of the background inhibition information synthesis image after adopting the method in the embodiment is greatly improved compared with that of the infrared intensity image.
What is not described in detail in the present specification is a well known technology to those skilled in the art.
Although the present invention has been described in terms of the preferred embodiments, it is not intended to be limited to the embodiments, and any person skilled in the art can make any possible variations and modifications to the technical solution of the present invention by using the methods and technical matters disclosed above without departing from the spirit and scope of the present invention, so any simple modifications, equivalent variations and modifications to the embodiments described above according to the technical matters of the present invention are within the scope of the technical matters of the present invention.
Claims (6)
1. The sea surface target detection method based on the multiband infrared image is characterized by comprising the following steps of:
step one, collecting infrared images of a plurality of wave bands of the same target scene;
secondly, carrying out background estimation on the collected infrared images of a plurality of wave bands by utilizing the characteristic of the multiband vector to obtain a background estimation vector; the background estimation vector obtaining method comprises the following steps: firstly, calculating the average value of the infrared image of each wave band, and then forming vectors by all the average values as background estimation vectors;
step three, calculating the distance and the included angle between the multiband feature vector of each pixel point in the target scene and the background estimation vector; the method comprises the following steps: firstly, calculating the gray scale of an infrared image of each wave band, and then forming a vector of the gray scale of the infrared image of each wave band as a multiband feature vector; finally, calculating the distance and the included angle between the multiband characteristic vector and the background estimation vector;
step four, synthesizing and calculating the distance and the included angle in the step three to obtain an image after background suppression;
and fifthly, dividing the image obtained in the step four by adopting a minimum error self-adaptive threshold method, and detecting a target position.
2. The method for detecting the sea surface target based on the multiband infrared image according to claim 1, wherein the infrared multiband imaging system based on rotary filtering is adopted to acquire the target scene.
3. The sea surface target detection method based on multiband infrared image according to claim 1, wherein infrared images of four wave bands of the same target scene are acquired; the wavelengths of the four wave bands are respectively: 3.7 μm-4.8 μm, 3.0 μm-3.3 μm, 3.4 μm-4.1 μm, 4.4 μm-4.9 μm.
4. The method for detecting the sea surface target based on the multiband infrared image according to claim 2, wherein the frame frequency of each band of the infrared multiband imaging system based on the rotary filtering is not lower than 80Hz.
5. A method of sea surface target detection based on multi-band infrared images according to any of claims 1-4, wherein the distance and angle combination is calculated as the product of the distance and angle of the multi-band feature vector and the background estimate vector.
6. The method for detecting a sea surface target based on multi-band infrared images according to any one of claims 1 to 4, wherein the image obtained in the fourth step is segmented by a minimum error adaptive thresholding method, and then centroid coordinates of the obtained segmented target region are calculated, thereby obtaining a desired target detection result.
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