An effective method for the detection and removal of thin clouds from MODIS image

Ruizhi Ren; Shuxu Guo; Lingjia Gu; Lang Wang; Xu Wang

doi:10.1117/12.825568

31 August 2009 An effective method for the detection and removal of thin clouds from MODIS image

Ruizhi Ren, Shuxu Guo, Lingjia Gu, Lang Wang, Xu Wang

Proceedings Volume 7455, Satellite Data Compression, Communication, and Processing V; 74550Z (2009) https://doi.org/10.1117/12.825568
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

Cloud is one of common noises in MODIS remote sensing image. Because of cloud interference, much important information covered with cloud can't be obtained. In this paper, an effective method is proposed to detect and remove thin clouds with single MODIS image. The proposed method involves two processing-thin cloud detection and thin cloud removal. As for thin cloud detection, through analyzing the cloud spectral characters in MODIS thirty-six bands, we can draw the conclusion that the spectral reflections of ground and cloud are different in various MODIS band. Hence, the cloud and ground area can be separately identified based on MODIS multispectral analysis. Then, the region label algorithm is used to label thin clouds from many candidate objects. After cloud detection processing, thin cloud removal method is used to process each cloud region. Comparing with traditional methods, the proposed method can realize thin cloud detection and removal with single remote sensing image. Additionally, the cloud removal processing mainly aims to the cloud label region rather than the whole image, so it can improve the processing efficiency. Experiment results show the method can effectively remove thin cloud from MODIS image.

Citation Download Citation

Ruizhi Ren, Shuxu Guo, Lingjia Gu, Lang Wang, and Xu Wang "An effective method for the detection and removal of thin clouds from MODIS image", Proc. SPIE 7455, Satellite Data Compression, Communication, and Processing V, 74550Z (31 August 2009); https://doi.org/10.1117/12.825568

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