shadow detection of man made buildings in high resolution panchromatic satellite images - 2014


High-resolution satellite imagery is considered an wonderful candidate for extracting info regarding the human activities on Earth. The knowledge regarding residential development and suburban area mapping is of interest that may be obtained from these pictures. Shadow of structures such as man-created buildings is one in all the main cues for structure detection in panchromatic high-resolution satellite imagery. However, to correctly exploit the knowledge of the shadow in an image, the shadow needs to be detected and isolated initial. During this paper, we propose a brand new algorithm for shadow detection and isolation of buildings in high-resolution panchromatic satellite imagery. The proposed algorithm is predicated on tailoring the ancient model of the geometric active contours such that the new model of the contours is systematically biased toward segmenting the shadow and also the dark regions in the image. The systematic biasing within the proposed contour model is accomplished by novel encoding of the radiometric characteristics of the shadows regions. When detecting and segmenting the shadow and the dark regions within the image, more processing steps are introduced. The proposed postprocessing is predicated on selection of optimal threshold and a boundary complexity metric to differentiate the true shadows from the litter. Experimental results are presented to validate the performance of the proposed algorithm on real high-resolution panchromatic satellite images.

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