A Gaussian proportional mixture model for sparse representation sar image de-speckling method

Abstract

The invention relates to a sparse representation SAR image speckle reduction method based on a Gaussian proportional mixture model, and belongs to the field of image filtering research. This method first establishes a sparse representation model of a single image block; then, based on the statistical characteristics of coherence spots and the Bayesian estimation principle, the sparse coefficients are represented by the GSM model to obtain an optimized model; at the same time, the SAR image is classified, and based on the classification results Establish a sparse model; finally, use the convex optimization method to solve the above model to obtain the optimal sparse representation, and then obtain the denoised image. This method can effectively suppress coherence spots while better retaining the detailed information of SAR images, and achieve good image reconstruction quality.

Description

technical field [0001] The invention relates to a sparse representation SAR image speckle reduction method based on a Gaussian proportional mixture model, which belongs to the field of image filtering research. Background technique [0002] Synthetic Aperture Radar (SAR) has become a representative radar system in the field of microwave remote sensing due to its high-resolution imaging capabilities in azimuth and range, and has attracted widespread attention in both military and civilian applications. When the radar emits electromagnetic signals to irradiate the target, the interference between the random scattering signal of the target and the transmitted signal will produce coherent speckle noise, which seriously affects the image quality, so the suppression of coherent speckle noise is particularly important. The most direct way to eliminate speckle noise is to use multi-view processing, but this method will reduce the azimuth resolution. A more reasonable way is to use f...

AI Technical Summary

Problems solved by technology

However, although the PPB algorithm can suppress the coherent speckle better, it will introduce a large number of artificial artifacts, resulting in a large loss of image detail information. The SAR-BM3D and FANS algorithms are relatively better in maintaining detail information, but the speckle reduction effect is not as good as PPB. , unable to suppress coherent speckle noise as much as possible

Images