High-Resolution SAR Image Despeckling Based on Nonlocal Means Filter and Modified AA Model

Author:

Ke Qiao1,Zeng-guo Sun2ORCID,Liu Yang3,Wei Wei4,Woźniak Marcin5ORCID,Scherer Rafał6ORCID

Affiliation:

1. School of Software, Northwestern Polytechnical University, Xi’an 710129, China

2. School of Computer Science, Shaanxi Normal University, Xi’an 710119, China

3. College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China

4. School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China

5. Institute of Mathematics, Silesian University of Technology, Kaszubska 23, Gliwice 44-100, Poland

6. Czestochowa University of Technology, Al. Armii Krajowej 36, Czestochowa 42-200, Poland

Abstract

A new speckle suppression algorithm is proposed for high-resolution synthetic aperture radar (SAR) images. It is based on the nonlocal means (NLM) filter and the modified Aubert and Aujol (AA) model. This method takes the nonlocal Dirichlet function as a linear regularization item, which constructs the weight by measuring the similarity of images. Then, a new despeckling model is introduced by combining the regularization item and the data item of the AA model, and an iterative algorithm is proposed to solve the new model. The experiments show that, compared with the AA model, the proposed model has more effective performance in suppressing speckle; namely, ENL and DCV measures are 21.75% and 4.5% higher, respectively, than for NLM. Moreover, it also has better performance in keeping the edge information.

Funder

China Postdoctoral Science Foundation

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

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