变序字典学习AO-DL的资源三号遥感影像云去除

doi:10.11947/j.AGCS.2017.20160474

测绘学报 ›› 2017, Vol. 46 ›› Issue (5): 623-630.doi: 10.11947/j.AGCS.2017.20160474

变序字典学习AO-DL的资源三号遥感影像云去除

陆婉芸^1,2, 王继周², 曹萌³

1. 辽宁工程技术大学测绘与地理科学学院, 辽宁阜新 123000;
2. 中国测绘科学研究院, 北京 100830;
3. 国家测绘工程技术研究中心, 北京 100039

收稿日期:2016-09-28 修回日期:2017-04-20 出版日期:2017-06-20 发布日期:2017-06-05
作者简介:陆婉芸(1992-),女,硕士,研究方向为遥感影像处理和地图制图学与地理信息工程。E-mail:lwy_happy6@163.com
基金资助:
国家重点研发计划（2016YFC0803100）；国家自然科学基金（41101435）

Cloud Removal in ZY-3 Remote Sensing Image Based on Atoms-reordered Dictionary Learning AO-DL

LU Wanyun^1,2, WANG Jizhou², CAO Meng³

1. Institute of Surveying and Geographic Science, Liaoning Technical University, Fuxin 123000, China;
2. Chinese Academy of Surveying and Mapping, Beijing 100830, China;
3. National Engineering Research Center of Surveying and Mapping, Beijing 100039, China

Received:2016-09-28 Revised:2017-04-20 Online:2017-06-20 Published:2017-06-05
Supported by:
The National Key Research and Development Plan (No.2016YFC0803100);The National Natural Science Foundation of China (No.41101435)

摘要/Abstract

摘要： 采用了一种压缩感知方法进行遥感影像去云。该方法以压缩感知为理论基础，在采用K-SVD字典学习与稀疏表示的正交匹配追踪算法（OMP）相结合的同时，在字典原子训练的过程中加入某种特定的排序规则，使得各个影像字典在拥有各自影像属性的同时其原子也具备相似的排列顺序，减小影像间差异的干扰，使得遥感影像受云和阴影污染区域的重建取得良好的效果。最后应用两组相同地区不同时域的资源三号卫星影像进行了试验验证。

关键词: 资源三号, 云去除, 字典训练, K-SVD, 稀疏表示

Abstract: In this paper, a new cloud removal method in remote sensing images is adopted.Based on the theory of compressive sensing,this method combines K-SVD dictionary learning with the orthogonal matching pursuit(OMP) algorithm of sparse representation.At the same time, a specific sorting rule is added to the process of dictionary atoms training, so that each image dictionary has its own image properties while its atoms also have a similar arrangement order to reduce the interference between image differences.In this method,the good effect of reconstruction of the contaminated region by clouds and shadows in remote sensing images is achieved.To illustrate the performance of the proposed method,experiments on two sets of data of multitemporal ZY-3 images at the same area are discussed.

Key words: ZY-3, cloud removal, dictionary learning, K-SVD, sparse representation

中图分类号:

P237

陆婉芸, 王继周, 曹萌. 变序字典学习AO-DL的资源三号遥感影像云去除[J]. 测绘学报, 2017, 46(5): 623-630.

LU Wanyun, WANG Jizhou, CAO Meng. Cloud Removal in ZY-3 Remote Sensing Image Based on Atoms-reordered Dictionary Learning AO-DL[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(5): 623-630.

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变序字典学习AO-DL的资源三号遥感影像云去除

Cloud Removal in ZY-3 Remote Sensing Image Based on Atoms-reordered Dictionary Learning AO-DL

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