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计算机工程 ›› 2012, Vol. 38 ›› Issue (04): 188-190. doi: 10.3969/j.issn.1000-3428.2012.04.061

• 图形图像处理 • 上一篇    下一篇

基于NSCT的遥感图像模糊增强算法

杜超本 1,贾振红 1,覃锡忠 1,杨 杰 2,胡英杰 3,李殿均 1   

  1. (1. 新疆大学信息科学与工程学院,乌鲁木齐 830046;2. 上海交通大学图像处理与模式识别研究所,上海 200240;3. 奥克兰理工大学知识工程与发现研究所,新西兰 奥克兰 1020)
  • 收稿日期:2011-08-04 出版日期:2012-02-20 发布日期:2012-02-20
  • 作者简介:杜超本(1987-),男,硕士研究生,主研方向:图像处 理;贾振红(通讯作者),教授、博士、博士生导师;覃锡忠,副教授;杨 杰,教授、博士、博士生导师;胡英杰,研究员、博士;李殿均,硕士研究生
  • 基金资助:
    科技部国际科技合作基金资助项目(2009DFA12870);教育部促进与美大地区科研合作与高层次人才培养基金资助项目(2010-1595)

Remote Sensing Image Fuzzy Enhancement Algorithm

DU Chao-ben 1, JIA Zhen-hong 1, QIN Xi-zhong 1, YANG Jie 2, HU Ying-jie 3, LI Dian-jun 1   

  1. (1. College of Information Science and Engineering, Xinjiang University, Urumuqi 830046, China; 2. Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China; 3. Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1020, New Zealand)
  • Received:2011-08-04 Online:2012-02-20 Published:2012-02-20

摘要: 针对传统小波变换增强方法无法调整图像亮度的问题,提出一种基于非下采样Contourlet变换(NSCT)的遥感图像模糊增强算法。对遥感图像进行NSCT变换,得到图像的高通子带和低通子带,在高通子带设置阈值,对大于阈值的高通子带系数进行线性增强,小于阈值的系数置为0,对低通子带进行模糊对比增强。实验结果表明,该算法能获得较好的图像平均值和熵值,视觉效果较优。

关键词: 遥感图像, 图像增强, 非下采样Contourlet变换, 模糊增强, 自适应阈值

Abstract: Traditional wavelet transformation enhancement can not adjust the brightness of an image effectively. Aiming at this problem, this paper proposes a remote sensing image fuzzy enhancement algorithm based on Nonsubsampled Contourlet Transform(NSCT). The remote sensing images are transformed into the high-pass sub-band and low-pass sub-band by NSCT, and the threshold is set in the high-pass sub-band, the high-pass subband coefficients which is greater than the threshold is enhanced by linear enhancement, the high-pass subband coefficients which less than the threshold is set zero, the low-pass subband is enhanced by the fuzzy contrast enhancement. Experimental results show the effectiveness of the method in the improvement of entropy and the average.

Key words: remote sensing image, image enhancement, Nonsubsampled Contourlet Transform(NSCT), fuzzy enhancement, adaptive threshold

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