CN116051426A - Synthetic aperture radar image processing method - Google Patents
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Abstract
The invention discloses a synthetic aperture radar image processing method, which relates to the technical field of radar image processing and comprises the steps of preprocessing an original image and selecting a target area T; calculating a gray scale interval H and a gray scale average value J of a target pixel in a target area T; establishing a mapping relation between the target pixel and the scattering information by using a Bayesian joint density function; and carrying out noise reduction processing on the radar image based on the mapping relation. The method has the advantages that the scattering information x corresponding to the target area A can be determined through the mapping relation established by the Bayesian joint density function, then the pixel points in the target area A are further identified according to the gray scale interval H and the gray scale average value J corresponding to the scattering information x, secondary denoising processing is carried out, the radar image is reconstructed, and the mapping relation between the SAR image and the scattering information can prevent some image information from being filtered out as noise, so that the image is incomplete, and the method is beneficial to distinguishing the target object according to the radar image.
Description
Technical Field
The invention relates to the technical field of radar image processing, in particular to a synthetic aperture radar image processing method.
Background
The synthetic aperture radar is mainly used for aviation measurement, aviation remote sensing, satellite ocean observation, aerospace reconnaissance, image matching guidance and the like. It can find hidden and disguised targets such as identifying disguised missile underground launch wells, identifying ground targets in cloud and fog covered areas, etc. In missile image matching guidance, a synthetic aperture radar image is adopted, so that a concealed and camouflaged target can be hit by the missile. Synthetic aperture radar is also used for deep space exploration, for example for exploration of geological structures of the moon, the golden star with synthetic aperture radar
The further application of the SAR image is seriously influenced by speckle noise, and the China patent with the application number of CN201711498074.2 discloses a synthetic aperture radar image denoising method, which is characterized in that two denoising algorithms are firstly used for denoising an SAR original image to be processed to obtain a fused denoising image, but the SAR image detail is distinguished even if the radar does not use a motion state and a detection angle, and the SAR image detail is also caused even though the radar does not use the motion state and the detection angle, the existing denoising method can save the local structure of the image, but does not link the SAR image with scattered information, so that some image information is easy to be filtered as noise in the denoising process, and the limitation exists.
Disclosure of Invention
The invention solves the technical problems that: in the existing method, no relation is established between the SAR image and the scattering information, and some image information is easily filtered out as noise in the denoising process, so that the method has limitations.
In order to solve the technical problems, the invention provides the following technical scheme: a synthetic aperture radar image processing method, comprising: preprocessing an original image, and selecting a target area T; calculating a gray scale interval H and a gray scale average value J of a target pixel in a target area T; establishing a mapping relation between the target pixel and the scattering information by using a Bayesian joint density function; and carrying out noise reduction processing on the radar image based on the mapping relation.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein: preprocessing the original image includes: acquiring an original image using a synthetic aperture radar device; the original image is converted into a first gray scale image.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein:
selecting the target region T comprises defining a region of the target object on the first gray image as the target region T, wherein the set of pixel points of the target region T is expressed as T= (a) 1,1 ,a 1,2 ,a 2,1 ,...,a m,n ) The calculation expression is as follows:
wherein,,
is an element in the target area T.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein: the calculation of the gray scale interval H and the gray scale average value J of all pixel points in the target area T includes: selecting all pixel points in the target area T, and taking the numerical value with the maximum and minimum gray values as a gray interval H; the average value of the gray values of all the pixel points in the target area T is taken as a gray average value J.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein: and taking the pixel point in the gray scale section H in the target area T as a target pixel.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein: the establishing of the mapping relation between the target pixel and the scattering information by using the Bayesian joint density function comprises the following steps: the mathematical expression of the bayesian joint density function is:
P(θ/(x 1 ,x 2 ,...,x n )）=P((x 1 ,x 2 ,...,x n )/θ)P(θ)/P(x 1 ,x 2 ,...,x n )
wherein P represents the gray value of the target pixel, θ represents the target pixel, (x) 1 ,x 2 ,...，x n ) Representing scattering information;calculating probability distribution of scattering information x corresponding to all pixel points in the target area T; and determining a radar target according to probability distribution of scattering information x corresponding to all pixel points in the target area T.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein: the noise reduction processing of the radar image comprises the following steps: collecting a radar image and converting the radar image into a second gray level image; screening pixel points in the second gray level image based on the gray level interval H to obtain a target pixel set; scanning pixel points around the pixel points based on an abscissa value and an ordinate value of the pixel points included in the target pixel set; the pixel value is located in the gray scale interval, and the adjacent pixel points are used as a second target area A; and filtering the pixel points outside the second target area A.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein: determining scattering information x corresponding to the second target area A based on the mapping relation; and identifying the pixel points in the second target area A according to the gray scale interval H and the gray scale average value J corresponding to the scattering information x.
As a preferable embodiment of the synthetic aperture radar image processing method of the present invention, wherein: and screening pixel points which accord with the gray scale interval H and the gray scale mean value J in the second target area A, and reconstructing a radar image.
The invention has the beneficial effects that: the mapping relation established by the Bayesian joint density function can determine the scattering information x corresponding to the second target area A, then further identify the pixel points in the second target area A according to the gray scale interval H and the gray scale mean value J corresponding to the scattering information x, perform secondary denoising processing, reconstruct a radar image, and prevent some image information from being filtered out as noise by the mapping relation between the SAR image and the scattering information, so that the image is incomplete, and the object identification according to the radar image is facilitated.
Drawings
Fig. 1 is a basic flow diagram of a method for processing an image of a synthetic aperture radar according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an off-hook synthetic aperture radar scan of a method for processing images of a synthetic aperture radar according to an embodiment of the present invention.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings.
Example 1
Referring to fig. 1, for one embodiment of the present invention, there is provided a synthetic aperture radar image processing method, including:
s1, preprocessing an original image and selecting a target area T. Comprising the following steps:
preprocessing the original image includes:
the original image is acquired using a synthetic aperture radar device. The method comprises the steps of collecting synthetic aperture radar image data, storing the collected data in a storage medium, and scanning a target object from different angles, directions and distances by microwave pulses with specific frequencies to obtain an original image of the target object, wherein the original image is taken as a sample.
The relative motion of the target and the synthetic aperture radar is utilized to complete space sampling through a single array element, and the wave front space sampling set acquired by the array antenna is replaced by echo time sampling sequences received by the single array element at different relative space positions. As long as the target is illuminated by the emitted energy lobe or within the beam width, the target is sampled and imaged to produce a SAR image.
The original image is converted into a first gray scale image.
By converting each pixel in the color radar image into a gray scale pixel, the whole image can be converted into a gray scale map, and the expression is as follows:
GRAY[Y]←BGR[A]=0.299*R+0.587*G+0.155*B
wherein RGB respectively represent colors.
The selecting of the target area T includes:
a region of the target object on the first gray level image is defined as a target region T, and a set of pixel points of the target region T is expressed as T= (a) 1,1 ,a 1,2 ,a 2,1 ,...,a m,n ) The calculation expression is as follows:
wherein a is m,n A, which is an element in the target area T m,n The coordinates in the first gray scale image are expressed as (m, n), m representing the pixel point a m,n N represents pixel point a m,n Is a m,n The larger the value is, the whiter the color is, and the gray value is 0 is black.
After the original image is converted into the first gray-scale image, a region representing the target object in the first gray-scale image can be defined as a target region T, and the target region T can be extracted.
S2, calculating a gray scale interval H and a gray scale average value J of target pixels in the target area T.
Selecting all pixel points in the target area T, and taking the numerical value with the maximum and minimum gray values as a gray interval H;
the average value of the gray values of all the pixel points in the target area T is taken as a gray average value J.
And taking the pixel point in the gray scale section H in the target area T as a target pixel.
And S3, establishing a mapping relation between the target pixel and the scattering information by using a Bayesian joint density function. Comprising the following steps:
the mathematical expression of the bayesian joint density function is:
P(θ/(x 1 ,x 2 ,...,x n )）=P((x 1 ,x 2 ,...,x n )/θ)P(θ)/P(x 1 ,x 2 ,...,x n )
wherein P represents the gray value of the target pixel, and θ represents the targetTarget pixel, (x) 1 ,x 2 ,...，x n ) Representing scattering information;
calculating probability distribution of scattering information x corresponding to all pixel points in the target area T;
and determining a radar target according to probability distribution of scattering information x corresponding to all pixel points in the target area T.
Different targets have different dielectric constants and surface roughness, scattering characteristics and penetrating power which are presented to the frequency, the penetrating angle and the polarization mode of microwaves are different, the corresponding gray values of pixels which are presented in a target area T are different through the scattering characteristics and the penetrating power, in a first gray level image, the gray value of one pixel possibly corresponds to a plurality of scattering information x, so that targets which need to be detected in focus, such as fighter plane, device vehicles or personnel, are scanned for a plurality of times when the synthetic aperture radar acquires an original image, the original image is acquired as a sample, at the moment, the gray values of the scattering information x and the target pixels are all known target parameters, a model of the mapping relation between the target pixels and the scattering information in the target area is optimized, and the accuracy of the targets is improved.
And S4, carrying out noise reduction processing on the radar image based on the mapping relation.
The noise reduction processing of the radar image comprises the following steps:
collecting a radar image and converting the radar image into a second gray level image;
screening pixel points in the second gray level image based on the gray level interval H to obtain a target pixel set; and preventing missing of the pixel points of the target features reflected in the second gray level image, so that feature missing is caused.
Scanning pixel points around the pixel points based on an abscissa value and an ordinate value of the pixel points included in the target pixel set;
the pixel value is located in the gray scale interval, and the adjacent pixel points are used as a second target area A;
and filtering the pixel points outside the second target area A. The speckle can be denoised according to the radar cross section reflected on the radar image. The synthetic aperture radar can identify the material of an object and has moving penetrating power, so that the synthetic aperture radar has different dielectric constants and surface roughness according to different targets, the scattering characteristics and the penetrating power of microwaves are different, the scattering characteristics and the penetrating power of the microwaves are different, the gray values of corresponding pixel points which are represented in a target area T are different, and the pixel points generated by some camouflage objects on the targets can be denoised, such as camouflage branches inserted on a tank, the scattering information generated by the branches and the tank is different, and the corresponding pixel points are different.
The second target area a can be extracted, and the background outside the second target area a can be filtered to remove noise, so that the operation amount can be reduced.
Determining scattering information x corresponding to the second target area A based on the mapping relation;
and further identifying the pixel points in the second target area A according to the gray scale interval H and the gray scale average value J corresponding to the scattering information x.
And screening pixel points which accord with the gray scale interval H and the gray scale mean value J in the second target area A, and reconstructing a radar image.
The gray value of the pixel point in the gray interval H of the SAR image generated by the SAR scanning in actual work is a known target parameter, the scattering information x corresponding to the second target area A can be determined through the mapping relation established by the Bayesian joint density function, then the pixel point in the second target area A is further identified according to the gray interval H and the gray average value J corresponding to the scattering information x, secondary denoising processing is carried out, the radar image is reconstructed, and the mapping relation between the SAR image and the scattering information can prevent some image information from being filtered as noise, so that the image is incomplete, and the target object is favorably distinguished according to the radar image.
Example 2
Referring to fig. 2, in another embodiment of the present invention, which is different from the first embodiment, an experimental verification of a synthetic aperture radar image processing method is provided, and in order to verify and explain the technical effects adopted in the method, the conventional technical scheme is adopted to perform a comparison test with the method, and the experimental results are compared by means of scientific demonstration to verify the true effects of the method.
The experiment adopts 1 model aircraft, 4 interference models are respectively A1 (balloon same model aircraft), A2 (plastic same model aircraft), A3 (wooden same model aircraft) and A4 (same model aircraft) which are respectively fixed on the ground, and then unmanned aerial vehicles outside 100 kilometers are used for carrying out the alignment of synthetic aperture radars for scanning.
Table 1: table of experimental records.
| A1 | A2 | A3 | A4 | ||
| Means of conventional technology | Is that | Is that | Is that | Whether or not | Whether or not to filter |
| The method | Is that | Is that | Is that | Is that | Whether or not to filter |
As can be seen from Table 1, the synthetic aperture radar can effectively identify different materials and filter the materials as noise, but in the process of noise reduction, the characteristic points reflected on the radar image cannot be completely and accurately identified, the characteristic points reflected on the radar image can be more accurately extracted by the method, different targets have different dielectric constants and surface roughness, the scattering characteristics and the penetrating power presented by the frequency, the penetrating angle and the polarization mode of microwaves are different, the corresponding gray values of the pixel points represented in the target area are different through the scattering characteristics and the penetrating power, the reverse connection of a radar image and the echo signals is favorably established by adopting the method, the target echo signals are accurately extracted from the echo signals mixed by the noise and the targets, the secondary denoising processing is performed, and the image is reconstructed by using the mapping relation between the SAR image and the scattering information, so that some image information is prevented from being filtered as noise, the image is incomplete, and the target object is favorably distinguished according to the radar image.
It should be appreciated that embodiments of the invention may be implemented or realized by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer readable storage medium configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, in accordance with the methods and drawings described in the specific embodiments. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
Claims (9)
1. A synthetic aperture radar image processing method, characterized by comprising:
preprocessing an original image, and selecting a target area T;
calculating a gray scale interval H and a gray scale average value J of a target pixel in a target area T;
establishing a mapping relation between the target pixel and the scattering information by using a Bayesian joint density function;
and carrying out noise reduction processing on the radar image based on the mapping relation.
2. The synthetic aperture radar image processing method according to claim 1, wherein:
preprocessing the original image includes:
acquiring an original image using a synthetic aperture radar device;
the original image is converted into a first gray scale image.
3. The synthetic aperture radar image processing method according to claim 2, wherein: the selecting of the target area T includes:
defining the region of the target object on the first gray scale imageIs defined as a target region T, and the set of pixel points of the target region T is represented as t= (a) 1,1 ,a 1,2 ,a 2,1 ,...,a m,n ) The calculation expression is as follows:
4. A synthetic aperture radar image processing method according to claim 3 wherein: the calculation of the gray scale interval H and the gray scale average value J of all pixel points in the target area T includes:
selecting all pixel points in the target area T, and taking the numerical value with the maximum and minimum gray values as a gray interval H;
the average value of the gray values of all the pixel points in the target area T is taken as a gray average value J.
5. The synthetic aperture radar image processing method of claim 4 wherein:
and taking the pixel point in the gray scale section H in the target area T as a target pixel.
6. The synthetic aperture radar image processing method of claim 5 wherein:
the establishing of the mapping relation between the target pixel and the scattering information by using the Bayesian joint density function comprises the following steps:
the mathematical expression of the bayesian joint density function is:
P(θ/(x 1 ,x 2 ,...,x n )）=P((x 1 ,x 2 ,...,x n )/θ)P(θ)/P(x 1 ,x 2 ,...,x n )
wherein P represents the gray value of the target pixel, θ represents the target pixel, (x) 1 ,x 2 ,...，x n ) Representing scattering information;
calculating probability distribution of scattering information x corresponding to all pixel points in the target area T;
and determining a radar target according to probability distribution of scattering information x corresponding to all pixel points in the target area T.
7. The synthetic aperture radar image processing method of claim 6 wherein:
the noise reduction processing of the radar image comprises the following steps:
collecting a radar image and converting the radar image into a second gray level image;
screening pixel points in the second gray level image based on the gray level interval H to obtain a target pixel set;
scanning pixel points around the pixel points based on an abscissa value and an ordinate value of the pixel points included in the target pixel set;
the pixel value is located in the gray scale interval, and the adjacent pixel points are used as a second target area A;
and filtering the pixel points outside the second target area A.
8. The synthetic aperture radar image processing method of claim 7 wherein:
determining scattering information x corresponding to the second target area A based on the mapping relation;
and identifying the pixel points in the second target area A according to the gray scale interval H and the gray scale average value J corresponding to the scattering information x.
9. The synthetic aperture radar image processing method of claim 8, wherein:
and screening pixel points which accord with the gray scale interval H and the gray scale mean value J in the second target area A, and reconstructing a radar image.
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