Non-Local Means De-Speckling Based on Multi-Directional Local Plane Inclination Angle

Author:

Guo Fengcheng1,Tang Haoran1,Liu Wensong1

Affiliation:

1. The School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China

Abstract

The unavoidable speckle in SAR images seriously interferes with image quality and has a negative effect on subsequent image interpretation. The existing filters still need to be strengthened in terms of both noise suppression and edge preservation. Based on this, a novel non-local means filter by multi-directional local plane inclination angle (MDLPIA) is proposed. The proposed filter uses the MDLPIA to reconstruct a new weight function for non-local means filtering. One instance of simulation data and four real SAR images are used for filtering experiments. In the experiment, seven other filters with excellent performance are selected for comparison, and six quantitative indicators are selected for algorithm performance evaluation. The experimental results show that the proposed filter achieves good visual and index evaluation results, and the equivalent number of looks (ENL) is at least 22.13 times higher than the unfiltered image. The effectiveness and superiority of the proposed algorithm are thus verified.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Science Foundation of Jiangsu Normal University

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference44 articles.

1. Pixel Difference Function and Local Entropy-Based Speckle Reducing Anisotropic Diffusion;Guo;IEEE Trans. Geosci. Remote Sens.,2022

2. A Practical Solution for SAR Despeckling With Adversarial Learning Generated Speckled-to-Speckled Images;Yuan;IEEE Geosci. Remote Sens. Let.,2022

3. SAR Image Speckle Reduction Based on Nonconvex Hybrid Total Variation Model;Sun;IEEE Trans. Geosci. Remote Sens.,2021

4. Unpaired Speckle Extraction for SAR Despeckling;Lin;IEEE Trans. Geosci. Remote Sens.,2023

5. Speckle-Free SAR Image Ship Detection;Chen;IEEE Trans. Image Process.,2021

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