The research on the shadow detection from high resolution remote sensing imagery

Shadow is one of the basic characteristics in urban remote sensed imagery. It affects the extraction of object’s edge, identification of objects and registration of images, so shadow detection has a great importance in urban remote sensing. In this paper, a kind of method with HSV is proposed to detect shadow from the color high resolution remote sensing imagery mainly through a series of processing steps including twice HSV transformation, self-adaptive segmentation, morphological closing operation and little area removing. At last, the ratio of the shadow is achieved according to the shadow area statistical analysis. The experiments show that the approach can detect the shadow accurately and availably.

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[4]  Touradj Ebrahimi,et al.  Cast shadow segmentation using invariant color features , 2004, Comput. Vis. Image Underst..

[5]  Stefan Hinz,et al.  Vehicle Detection in Aerial Images Using Generic Features, Grouping, and Context , 2001, DAGM-Symposium.

[6]  Qiming Qin,et al.  Shadow Segmentation and Compensation in High Resolution Satellite Images , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.