Building Shadow Detection with Integrated Characteristic Components for High Resolution Remote Sensing Images

doi:10.13474/j.cnki.11-2246.2018.0316

Abstract

Abstract: An object-oriented building shadow extraction method is proposed for high-resolution remote sensing images,which integrates the images characteristic components and the shadow's morphological characteristics of buildings.By analyzing the spectral characteristics of remote sensing images,the first component (PC₁),the green band component (G),the excess green (EXG) and the hue characteristic (H) were constructed,then we used the gamma transform to enhance the H band,and normalized the DN value of each characteristic component and made a comprehensive analysis.According to the morphological characteristics of building shadow,we established the area and aspect ratio rule and built a rule set.Thereby,the object-oriented building shadow information extraction was achieved.Finally,we selected remote sensing images from different regions and time intervals to extract building shadow.Experimental result showed that the proposed method can not only effectively reduce the influence of water bodies,vegetation and dark objects,but also remove the shadow of non-building structures,and then obtain integral building shadow patches without fragmentation.

Key words: high-resolution remote sensing image, shadow detection, characteristic component, morphological feature, object-oriented

CLC Number:

P237

XIE Yakun, FENG Dejun, LI Qiang, WANG Yinru, HU Minjun. Building Shadow Detection with Integrated Characteristic Components for High Resolution Remote Sensing Images[J]. 测绘通报, 2018, 0(10): 61-65.

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