Transform domain non local and minimum mean square error-based SAR (Synthetic Aperture Radar) image denoising method

Abstract

The invention discloses a transform domain non local and minimum mean square error-based SAR (Synthetic Aperture Radar) image denoising method which mainly solves the problems of edge excessive smoothness during denoising of an SAR image and difficulty in keeping point targets in the prior art. The transform domain non local and minimum mean square error-based SAR image denoising method comprises the following steps of: inputting an SAR image Y, processing one-layer non-subsample Laplace decomposition on the SAR image Y to obtain a low-frequency image YL and a high-frequency image YH; filtering the YL by using a PPB (Probalistic Patch-Based) filter to obtain a filtered image, carrying out shear wave filter decomposition on the YH to obtain a high-frequency subband image of each direction; modeling by using a Gaussian mixture model and denoising by using MMSE (Minimum Mean Square Error) estimation to obtain denoised high-frequency subband diaphragms; carrying out inverse shear wave transform on the low-frequency image YL and the high-frequency image YH to obtain a space domain image YZ; and classifying the YZ to obtain a final denoising result. The transform domain non local and minimum mean square error-based SAR image denoising method is capable of removing noise in a homogeneous region and well keeping clear edges of the images, and can be used for preprocessing the images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to the denoising of synthetic aperture radar SAR images, in particular to a SAR image denoising method based on transform domain non-local and minimum mean square error MMSE estimation, which can be used in the image preprocessing stage . Background technique [0002] Synthetic aperture radar has the characteristics of all-day, all-weather imaging, high-altitude resolution and strong penetration capability, so SAR images have been widely used in military and civilian applications. However, due to the limited resolution and coherence of the system, a kind of speckle noise is always unavoidable in the SAR imaging process. The existence of speckle noise seriously affects the quality of SAR image. SAR image denoising needs to effectively suppress noise in homogeneous areas. At the same time, it is also necessary to keep important information such as edges and point targets from...

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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the point target is difficult to maintain and the edge is easy to blur in SAR image denoising, and a SAR image denoising method based on non-local and minimum mean square error estimation in the transform domain is proposed to effectively suppress homogeneous Keep image edges and point targets clear while removing noise in the area, and improve the denoising effect

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