A Cloud Detection Method for High Resolution Remote Sensing Imagery Based on the Spectrum and Texture of Objects

被引：0

作者：

Dong Z. ^{[1
]}

Wang M. ^{[1
,2
]}

Li D. ^{[1
,2
]}

Wang Y. ^{[1
]}

Zhang Z. ^{[1
]}

机构：

[1] State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan

[2] Collaborative Innovation Center of Geospatial Technology, Wuhan

来源：

Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | 2018年 / 47卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Adaptive spectral threshold for cloud detection; Cloud detection; High resolution remote sensing image; LBP texture; Superpixels;

D O I：

10.11947/j.AGCS.2018.20170690

中图分类号：

学科分类号：

摘要：

To solving the problems that the spectral threshold selection of image cloud detection and the influence of cloud-like ground objects on cloud detection results,a novel cloud detection method for HSRI based onthe spectrum and texture of objects is proposed.Firstly,histogram equalization is performed on the image,and then the appropriate image cloud detection spectral threshold is obtained according to the image equalization histogram.Secondly,the image is segmented to obtain superpixels using the simple linear iterative clustering algorithm.The cloud in the image is initially detected based on cloud detection threshold and spectral attributes of superpixels.Thirdly,the local binary patterns (LBP) texture image of histogram equalization image is obtained.The initial cloud detection image is refined based on the gray mean value and angular second moment of the superpixels LBP texture to eliminate the influence of cloud like objects.Finally,the cloud detection image is processed using region growing algorithm and expansion algorithm to obtain accurate cloud detection results.The experimental results show that the proposed method can obtain good cloud detection results. © 2018, Surveying and Mapping Press. All right reserved.

引用

页码：996 / 1006

页数：10

共 27 条

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