Multi-Band Contourlet Transform For Adaptive Remote Sensing Image Denoising

被引:5
作者
Wang, Haijiang [1 ]
Wang, Jingpu [2 ]
Yao, Fuqi [3 ]
Ma, Yongqiang [1 ]
Li, Lihong [1 ]
Yang, Qinke [4 ]
机构
[1] Hebei Univ Engn, Sch Informat & Elect Engn, 199 St Guangming, Handan 056038, Hebei, Peoples R China
[2] Ludong Univ, Sch Resources & Environm Engn, 186 St Hongqi, Yantai 264025, Shandong, Peoples R China
[3] Changjiang River Sci Res Inst, Inst Agr Water Conservancy, 23 St Huangpu, Wuhan 430012, Hubei, Peoples R China
[4] Northwest Univ, Dept Urban & Resource Sci, 1 St Xuefu, Xian 710127, Shanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
contourlet; wavelet; M-band; remote sensing images; denoising; CURVELET TRANSFORM; SENSED IMAGES; WAVELET; REDUCTION; ENHANCEMENT;
D O I
10.1093/comjnl/bxz073
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The ability to remove noise from remote sensing images, while retaining the important features of the images, is becoming increasingly important. In this paper, we introduce the multi-band contourlet transform, a new method for adaptively denoising remote sensing images. We describe existing methods that use multi-resolution analysis transforms for denoising images and discuss their respective advantages and disadvantages. We then introduce our novel denoising method, which exploits the advantages of existing methods. We summarize the results of a comprehensive set of experiments designed to evaluate the performance of our method and compare it with the performance of existing methods. The results demonstrate that our method is superior to existing methods, both in terms of its ability to denoise images and to retain salient features of those images following denoising.
引用
收藏
页码:1084 / 1098
页数:15
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