Self-adaptive noise-containing SAR image full-variation segmentation method

Abstract

The invention belongs to the technical field of digital image processing, and particularly relates to a self-adaptive noise-containing SAR image variational segmentation method. According to the invention, a self-adaptive edge detection operator is introduced to control the diffusion of all-variation rule items, and a noise-containing SAR image segmentation variation model is built according to the reconstructed data items of a multiplicative noise distribution function. The model has the characteristics of non-linear, non-convex and non-smoothness performances, and is difficult to solve. According to a curve evolution theory and a operator splitting method, the minimization energy functional problem is formalized as the minimum value problem with the constraint. Meanwhile, a fast numerical approximation iterative solution method is designed to carry out SAR image segmentation. According to the invention, the self-adaptive noise-containing SAR image full-variation segmentation method is good in robustness for the multiplicative noise of SAR images, and the edge details can be well kept. The noise-containing SAR image segmentation is realized. Meanwhile, the method lays a foundationfor the interpretation analysis and other subsequent applications on SAR images. The method is friendly in application environment and wide in market prospect.

Description

Technical field: [0001] The invention belongs to the technical field of digital image processing, and in particular relates to an adaptive noise-containing SAR image variational segmentation method. Background technique: [0002] Synthetic Aperture Radar (SAR) image segmentation is the basic problem of image interpretation and analysis. The inherent coherent speckle noise makes the segmentation of SAR images more difficult. Filter and denoise, and then use optical image segmentation method for segmentation. However, in order to remove the multiplicative speckle noise, it is necessary to increase the filter, and the image edge details are often lost during denoising, and it is difficult to obtain accurate results by segmenting the denoised image as input. [0003] The processing methods involved in the prior art are more focused on the segmentation while suppressing speckle noise. The common noisy SAR image segmentation methods include segmentation based on Markov random fie...

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Problems solved by technology

[0004] The purpose of the present invention is to overcome the defects existing in the existing SAR segmentation method, seek to design a kind of self-adaptive noise-containing SAR image total variation segmentation method, introduce the adaptive edge detection operator to control the diffusion of the total variation rule item, according to the multiplicative The noise distribution function reconstructs the data item to establish a variational model of noisy SAR image segmentation, and based on the Alternating Direction Method of Multipliers (ADMM for short), cleverly designs auxiliary variables, through L 2 Norm constraints, to achieve the solution of the energy equation minimization extremum problem

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