遥感影像条带噪声去除的小波变分法

doi:10.11947/j.AGCS.2019.20180394

测绘学报 ›› 2019, Vol. 48 ›› Issue (8): 1025-1037.doi: 10.11947/j.AGCS.2019.20180394

遥感影像条带噪声去除的小波变分法

王昶^1,2, 张永生², 王旭³, 纪松²

1. 辽宁科技大学土木工程学院, 辽宁鞍山 114051;
2. 信息工程大学地理空间信息学院, 河南郑州 450001;
3. 辽宁生态工程职业学院林学院, 辽宁沈阳 110101

收稿日期:2018-08-21 修回日期:2019-02-27 出版日期:2019-08-20 发布日期:2019-08-27
作者简介:王昶(1983-),男,博士生,讲师,研究方向为遥感影像处理。E-mail:wangchang324@163.com
基金资助:
国家自然科学基金（41671409；41401534）

Stripe noise removal of remote image based on wavelet variational method

WANG Chang^1,2, ZHANG Yongsheng², WANG Xu³, JI Song²

1. School of Civil Engineering, University of Science and Technology Liaoning, Anshan 114051, China;
2. Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China;
3. Forestry Institute, Liaoning vocational college of ecological engineering, Shenyang 110101, China

Received:2018-08-21 Revised:2019-02-27 Online:2019-08-20 Published:2019-08-27
Supported by:
The National Natural Science Foundation of China(Nos. 41671409;41401534)

摘要/Abstract

摘要： 为了避免条带噪声去除过程中丢失影像细节，提出一种基于小波变分法去除遥感影像条带噪声。首先，对含有条带噪声的遥感影像进行小波分解；其次，通过构建的条带保留变分模型（SPVM）去除低层高频分量（含条带噪声）中的细节信息而保留条带噪声，从而有效分离出低层高频分量（含条带噪声）中的细节信息；通过构建的条带去除变分模型（DVM）去除高层高频分量（含条带噪声）中的条带噪声，从而有效地保留高层高频分量（含条带噪声）中的细节信息；最后，通过小波重构，获得去噪影像。试验证明本文方法在去除条带噪声的同时基本没有丢失影像细节，去噪后的影像对比度及质量都是最优的。

关键词: 小波变换, 条带保留变分模型, 条带去除变分模型, 高频分量, 遥感影像

Abstract: In order to avoid the loss of image details in the process of strip noise removal, a method based on wavelet variational method was proposed to remove strip noise of remote images. First, remote image with stripe noise was decomposed by wavelet technology. Second, a stripe preserve variation model was constructed, this model could effectively remove image details from the wavelet horizontal direction high-frequency components in lower layers and only preserve the stripe noise, and the details are effectively separated; a destriping variation model was constructed, this model could effectively preserve the image details while removing the strip noise form the wavelet horizontal direction high-frequency components in the top layers. Finally, the destriping image was obtained by wavelet reconstruction. Experimental results show that the proposed method not only can effectively restrain the stripe noise of remote image, and can be also preserve the image details very well. The quality and contrast of destriping image are the best.

Key words: wavelet transform, stripe preserve variation model, destriping variation model, high-frequency component, remote image

中图分类号:

P237

王昶, 张永生, 王旭, 纪松. 遥感影像条带噪声去除的小波变分法[J]. 测绘学报, 2019, 48(8): 1025-1037.

WANG Chang, ZHANG Yongsheng, WANG Xu, JI Song. Stripe noise removal of remote image based on wavelet variational method[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(8): 1025-1037.

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遥感影像条带噪声去除的小波变分法

Stripe noise removal of remote image based on wavelet variational method

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