Multi-band contourlet transform for adaptive remote sensing image denoising

被引:0
|
作者
Wang H. [1 ]
Wang J. [2 ]
Yao F. [3 ]
Ma Y. [1 ]
Li L. [1 ]
Yang Q. [4 ]
机构
[1] School of Information and Electrical Engineering, Hebei University of Engineering, No. 199, Street, Guangming, Handan, Province Hebei
[2] School of Resources and Environmental Engineering, Ludong University, No. 186, Street Hongqi, Yantai, Province Shandong
[3] Institute of Agricultural Water Conservancy, Changjiang River Scientific Research Institute, No. 23, Street Huangpu, Wuhan, Province Hubei
[4] Department of Urban and Resource Sciences, Northwest University, No. 1, Street, Xuefu, Xi’an, Province Shanxi
来源
Computer Journal | 2021年 / 63卷 / 07期
基金
中国国家自然科学基金;
关键词
Contourlet; Denoising; M-band; Remote sensing images; Wavelet;
D O I
10.1093/COMJNL/BXZ073
中图分类号
学科分类号
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. © The British Computer Society 2019. All rights reserved.
引用
收藏
页码:1084 / 1098
页数:14
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