计算机应用 ›› 2012, Vol. 32 ›› Issue (03): 746-748.DOI: 10.3724/SP.J.1087.2012.00746

• 图形图像技术 • 上一篇    下一篇

基于形态Haar小波的SAR图像斑点噪声抑制方法

李敏,张自友,卢林菊   

  1. 乐山师范学院 物理与电子工程学院,四川 乐山 614000
  • 收稿日期:2011-08-23 修回日期:2011-11-07 发布日期:2012-03-01 出版日期:2012-03-01
  • 通讯作者: 李敏
  • 作者简介:李敏(1977-),女,四川汉源人,副教授,硕士研究生,主要研究方向:图像处理、信号处理、小波分析应用;张自友(1979-),男,四川成都人,讲师,硕士研究生,主要研究方向:电子技术、计算机控制;卢林菊(1975-),女,四川华蓥人,讲师,主要研究方向:高频电子线路、传感器应用。
  • 基金资助:

    四川省教育厅自然科学重点项目(09ZA044)。

Speckle reduction of SAR image based on morphological Haar wavelet

LI Min, ZHANG Zi-you, LU Lin-ju   

  1. College of Physics and Electronic Engineering, Leshan Normal University, Leshan Sichuan 614000, China
  • Received:2011-08-23 Revised:2011-11-07 Online:2012-03-01 Published:2012-03-01
  • Contact: Min LI
  • Supported by:

    Sichuan Provincial Department of Education Natural Science Key Project

摘要: 针对现有相干斑抑制算法不能在去除斑点噪声和保持图像边缘、细节信息之间做到很好的折中,提出了一种新的基于形态Haar小波变换的合成孔径雷达(SAR)图像斑点噪声抑制方法。该方法首先对SAR图像进行二维形态Haar小波分解,图像的边缘、细节和纹理信息在低频子带中得到了更好的保留,噪声主要分布在高频子带;然后,根据各高频子带噪声的特点,分别对高频子带进行均值和中值滤波达到去除斑点噪声的目的;最后,再对低频子带和处理后的高频子带进行形态Haar小波精确重构得到去斑图像。实验证明:该算法不仅大大改善了原始SAR图像的画面质量,同时很好地保持了原始SAR图像的纹理特性和细节信息;该算法去斑性能指标总体优于传统的Lee滤波、Frost滤波、Kuan滤波和小波软阈值法。

关键词: 合成孔径雷达, 形态Haar小波, 斑点噪声抑制, 滤波, 细节保持

Abstract: The existing speckle reduction algorithms of Synthetic Aperture Radar (SAR) image can efficiently reduce the speckle effects but unfortunately smear edges and details. A new method, based on morphological Haar wavelet, was proposed. In this method, the SAR image was firstly decomposed by 2-D morphological Haar wavelet. Thus, the edges, details and textures were well preserved in low-frequency sub-band. The speckle noise was mainly distributed in high-frequency sub-bands. Then, the average filtering and median filtering were run on the corresponding high frequency sub-bands according to the noise features. Finally, 2-D morphological Haar wavelet inverse transform was carried on to low-frequency sub-band coefficients and filtered high-frequency sub-bands coefficients to reconstruct SAR image accurately. The experimental results show that the proposed method can not only filter the speckle noise efficiently, but well preserve the image textures and details of SAR image. The proposed method is better than the traditional Lee filtering, Frost filtering, Kuan filtering and wavelet soft-threshold overall.

Key words: Synthetic Aperture Radar (SAR), morphological Haar wavelet, speckle reduction, filtering, detail preservation

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