SAR image sparsing denoising method based on change detection

Abstract

The invention discloses an SAR image sparsing denoising method based on change detection. The SAR image sparsing denoising method includes the steps of firstly, inputting an image; secondly, obtaining a changed area image; thirdly, setting a change classification; fourthly, obtaining a two-classification binary image; fifthly, obtaining a two-area image; sixthly, conducting denoising on unchanged areas; seventhly, estimating noise standard deviation; eighthly, obtaining a synthetic image; ninthly, conducting sparsing dictionary denoising; tenthly, outputting a result. The denoising preprocessing is conducted for the SAR image change detection, and the SAR image sparsing denoising method has the advantages that the consistency of a changed area is kept well, the noise of an unchanged area can be well restrained, meanwhile, the texture detail information, outline detail information and edge detail information of an SAR image, especially of the changed area which has great influence on change detection at later period are reserved, scratches produced after denoising is conducted on the image are eliminated, the pseudo information produced when noise is restrained is reduced, and the accuracy of the change detection is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a change detection-based synthetic aperture radar (Synthetic Aperture Radar, SAR) image sparse denoising method in the field of change detection. The invention can be used for denoising and preprocessing SAR image change detection, and can effectively improve the accuracy of SAR image change detection. Background technique [0002] Image denoising technology solves the problem of image quality degradation caused by various noise interferences in the process of image acquisition, encoding and transmission, and improves image quality. It is an important link and research content in image processing. SAR image denoising can maintain the details of the image on the basis of effectively suppressing coherent speckle noise. [0003] Generally, the processing after denoising is the segmentation and classification of the SAR image, which is for a single image. However, fo...

AI Technical Summary

Problems solved by technology

Although this method can suppress the noise in the homogeneous area while maintaining the detailed information, it still has the disadvantage that the error control in the dictionary learning is easy to cause the loss of part of the texture information of the image in the actual operation, and increase the false detection rate of the later change detection.

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