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改进的BiShrink与DTCWT相结合的遥感图像去噪
引用本文:李明慧,贾振红,杨杰,Raphael Hu,李殿均. 改进的BiShrink与DTCWT相结合的遥感图像去噪[J]. 光电子.激光, 2012, 0(6): 1201-1205
作者姓名:李明慧  贾振红  杨杰  Raphael Hu  李殿均
作者单位:新疆大学信息科学与工程学院;新疆大学信息科学与工程学院;上海交通大学图像处理与模式识别研究所;奥克兰理工大学知识工程与开发研究所;新疆大学信息科学与工程学院
基金项目:科技部国际科技合作(2009DFA12870);教育部促进与美大地区科研合作与高层次人才培养资助项目
摘    要:
基于双树复数小波变换(DTCWT)良好的平移不变性和多方向选择性,以及尺度内DTC-WT系数的领域相关性,提出了一种bivariate shrinkage(BiShrink)的改进算法,对遥感图像进行去噪处理。实验结果表明,经本文算法降噪后,图像的峰值信噪比(PSNR)得到显著提高,较好地保持图像的边缘和细节信息,并抑制混淆现象。

关 键 词:双树复数小波变换(DTCWT)  bivariate shrinkage(BiShrink)阈值  领域相关性  遥感图像去噪

Remote sensing image denoising based on the combination of the improved BiShrink and DTCWT
LI Ming-hui,JIA Zhen-hong,YANG Jie,Raphael Hu and LI Dian-jun. Remote sensing image denoising based on the combination of the improved BiShrink and DTCWT[J]. Journal of Optoelectronics·laser, 2012, 0(6): 1201-1205
Authors:LI Ming-hui  JIA Zhen-hong  YANG Jie  Raphael Hu  LI Dian-jun
Affiliation:College of Information Science and Engineering,Xinjiang University,Urumuqi 830046,China;College of Information Science and Engineering,Xinjiang University,Urumuqi 830046,China;Institute of Image Processing and Pattern Recognition,Shanghai Jiao Tong University,Shanghai 200240,China;Knowledge Engineering and Discovery Research Institute,Auckland University of Technology,Auckland 1020,New Zealand;College of Information Science and Engineering,Xinjiang University,Urumuqi 830046,China
Abstract:
By considering the advantages of the dual tree complex wavelet transfer(DTCWT)in shift invariance and multi-direction selection,as well as the neighboring coefficients of DCTWT,an improved bivariate shrinkage(BiShrink) algorithm is presented to denoise the remote sensing images.Experimental results show that the proposed algorithm gets better peak signal-to-noise ratio(PSNR) than other methods obviously.In terms of visual quality,the proposed algorithm can achieve images with more details and edges,smooth profiles and restricted aliasing.
Keywords:dual-tree complex wavelet transfer(DTCWT)  bivariate shrinkage(BiShrink) threshold  neighboring coefficients  remote sensing image denoising
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