Cloud removal of remote sensing image based on multi-output support vector regression 被引量：2

Cloud removal of remote sensing image based on multi-output support vector regression

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摘要 Removal of cloud cover on the satellite remote sensing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet transform is used to achieve multi-scale decomposition of the area of thin cloud cover on remote sensing images. Through enhancing coefficients of high frequency and suppressing coefficients of low frequency, the thin cloud is removed. For thick cloud cover, if the areas of thick cloud cover on multi-source or multi-temporal remote sensing images do not overlap, the multi-output support vector regression learning method is used to remove this kind of thick clouds. If the thick cloud cover areas overlap, by using the multi-output learning of the surrounding areas to predict the surface features of the overlapped thick cloud cover areas, this kind of thick cloud is removed. Experimental results show that the proposed cloud removal method can effectively solve the problems of the cloud overlapping and radiation difference among multi-source images. The cloud removal image is clear and smooth. Removal of cloud cover on the satellite remote sensing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet transform is used to achieve multi-scale decomposition of the area of thin cloud cover on remote sensing images. Through enhancing coefficients of high frequency and suppressing coefficients of low frequency, the thin cloud is removed. For thick cloud cover, if the areas of thick cloud cover on multi-source or multi-temporal remote sensing images do not overlap, the multi-output support vector regression learning method is used to remove this kind of thick clouds. If the thick cloud cover areas overlap, by using the multi-output learning of the surrounding areas to predict the surface features of the overlapped thick cloud cover areas, this kind of thick cloud is removed. Experimental results show that the proposed cloud removal method can effectively solve the problems of the cloud overlapping and radiation difference among multi-source images. The cloud removal image is clear and smooth.

作者 Gensheng Hu Xiaoqi Sun Dong Liang Yingying Sun

机构地区 Key Laboratory of Intelligent Computing and Signal Processing School of Electronics and Information Engineering

出处《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第6期1082-1088,共7页 系统工程与电子技术（英文版）

基金 supported by the National Natural Science Foundation of China(61172127) the Natural Science Foundation of Anhui Province(1408085MF121)

关键词 remote sensing image cloud removal support vector regression multi-output remote sensing image,cloud removal,support vector regression,multi-output

分类号 TP751 [自动化与计算机技术—检测技术与自动化装置]

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参考文献1

1Yan Zhang,Yiyun Man.Satellite Image Adaptive Restoration Using Periodic Plus Smooth Image Decomposition and Complex Wavelet Packet Transforms[J].Tsinghua Science and Technology,2012,17(3):337-343. 被引量：2

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