Artificial Intelligence for Communications and Networks. Second EAI International Conference, AICON 2020, Virtual Event, December 19-20, 2020, Proceedings

Research Article

An Optimized Lee Filter Denoising Method Based on EIP Correction

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  • @INPROCEEDINGS{10.1007/978-3-030-69066-3_37,
        author={Yipeng Liu and Guoxing Huang and Weidang Lu and Hong Peng and Jingwen Wang},
        title={An Optimized Lee Filter Denoising Method Based on EIP Correction},
        proceedings={Artificial Intelligence for Communications and Networks. Second EAI International Conference, AICON 2020, Virtual Event, December 19-20, 2020, Proceedings},
        proceedings_a={AICON},
        year={2021},
        month={7},
        keywords={SAR Image filter Gray histogram Lee filter},
        doi={10.1007/978-3-030-69066-3_37}
    }
    
  • Yipeng Liu
    Guoxing Huang
    Weidang Lu
    Hong Peng
    Jingwen Wang
    Year: 2021
    An Optimized Lee Filter Denoising Method Based on EIP Correction
    AICON
    Springer
    DOI: 10.1007/978-3-030-69066-3_37
Yipeng Liu1, Guoxing Huang1, Weidang Lu1, Hong Peng1, Jingwen Wang2
  • 1: Zhejiang University of Technology
  • 2: China Jiliang University

Abstract

The speckle noise inherent in synthetic aperture radar (SAR) images seriously affects the visual effect of the image and brings difficulties to the subsequent parameter inversion and interpretation. However, the existing SAR image filtering methods are not effective in preserving the image edge details. In this paper, an exponential image processing (EIP) correction based lee filter denoising method is proposed to solve this problem. This method carried out a reasonable fuzzy division on the image gray histogram, and extracted its statistical characteristics from it. Such feature is used to correct the image based on the mathematical structure of EIP, and divide the filter area of the image to avoid the loss of edge information and dark details of the image. Simulation results have shown that the proposed method outperform the traditional methods in suppressing noise and protecting edge details.