SAR image de-noising algorithm based on Primal Sketch classification and SVD domain improvement MMSE estimation

An image and algorithm technology, applied in the field of image denoising, which can solve problems such as difficulty in maintaining point targets and easy blurring of edges.

CN104732493AInactive Publication Date: 2015-06-24XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2015-06-24
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses an SAR image de-noising algorithm based on Primal Sketch classification and SVD domain improvement MMSE estimation. The problem that in the prior art, details are fuzzy during SAR image de-noising is solved. The method mainly comprises the steps that firstly, in the Primal Sketch algorithm, an energy image is improved by the adoption of a dual-neighbourhood contrast enhancement method, then the Primal Sketch algorithm is adopted for dividing SAR images into a non-edge class and an edge class; NLSVD decomposition is carried out on the pixel points in the two classes, a singular value matrix is estimated by the minimum mean square error criterion containing constriction factors, and inverse transformation is carried out to obtain the estimation value of the edge class and the estimation value of the non-edge class; finally, edge coefficients are calculated, and the boundary of the edge class and the boundary of the non-edge class are fused through the Butterworth fusion method to obtain a de-noising result. According to the SAR image de-noising algorithm, speckle noise in the SAR image can be effectively removed, and the edge and point target information is well kept.
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Description

technical field

[0001] The invention belongs to the technical field of image denoising, and relates to the denoising of synthetic aperture radar SAR images, in particular to a SAR image denoising algorithm based on Primal Sketch classification and SVD domain improved MMSE estimation. Background technique

[0002] The emergence of synthetic aperture radar technology is a very important milestone in the development of radar technology. Its all-weather and all-weather detection capabilities, high resolution and strong penetration capabilities make it widely used in military and civilian applications. However, due to the mutual interference between electromagnetic waves during the propagation process, the superposition of the same phase is enhanced, and the amplitude of the anti-phase superposition is zero, resulting in some spots in the SAR image with random and drastic changes in brightness and darkness, that is, coherent speckle noise. The existence of coherent speckle noise ...

Examples

Embodiment Construction

[0063] figure 1 It is a flow chart of the present invention; the present invention provides a kind of SAR image denoising algorithm based on PrimalSketch classification and SVD domain improvement MMSE estimation, comprises the steps:

[0064] Step 1: Input a SAR image Y, the size of the image is M×N, M and N are the number of pixels in the row and column of the image respectively;

[0065] Step 2: Use a local filter bank to convolve each pixel of the input image Y, and solve the joint response, and combine the convolution value corresponding to the maximum response value in the joint response with the direction θ of the filter m , as the energy value and direction of the pixel respectively, traverse all the pixels to get the energy image ES and direction image ER;

[0066] 2a) Filter the input image Y, the local filters used are Gauss-Laplace (LoG) filter, Gaussian offset difference (DooG) filter and odd symmetric Gaussian offset difference (osDooG) filter Three categories. ...