3 November 2005 Building shadow detection in quickbird imagery using normalized multi-spectral data based on object-based classification
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Proceedings Volume 6043, MIPPR 2005: SAR and Multispectral Image Processing; 60430Q (2005) https://doi.org/10.1117/12.654859
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China
Building shadows are very integral parts in the high spatial resolution remote sensing images, especially in urban region. For this reason, shadow detection is a very important step in remote sensing imagery interpretation. Two kinds of method for shadow detection have been developed: color-based and model-based, but the both methods have their disadvantages: the former couldn't differentiate the objects which have similar color property with the shadow; the latter required other data for assistance. An effective approach to building shadow detection in Quickbird multi-spectral imagery is presented in this paper. The method is based on normalized multi-spectral data and object-based classification technology. By analyzing the spectral and geometrical characteristic of shadow region, the procedure is divided into three stages: 1) normalized multi-spectral imagery is obtained, by using 4 single band image data divide the sum of the four band data (similar with the normalized rgb); 2) using the blue and near infrared band of the normalized multi-spectral imagery to determine a threshold to extract shadow candidate regions; 3) an information integration stage confirmed or rejected each detected candidate image object by using object-based classification technology. Experimental results show that the proposed algorithm is efficient in detecting building shadow for Quickbird imagery.
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Xin Shen, Xin Shen, Xiaodong Zhang, Xiaodong Zhang, Deren Li, Deren Li, Jingang Hu, Jingang Hu, } "Building shadow detection in quickbird imagery using normalized multi-spectral data based on object-based classification", Proc. SPIE 6043, MIPPR 2005: SAR and Multispectral Image Processing, 60430Q (3 November 2005); doi: 10.1117/12.654859; https://doi.org/10.1117/12.654859

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