期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B3
页码：808-810
出版社：Copernicus Publications
摘要：Due to high object density and high proportion of shadow-covered areas, it is usually quite difficult to extract information in urban high-resolution airborne images from Leica Geosystems' airborne multispectral line sensor, ADS40. The shadows of various extent cause problem in image matching for elevation extraction, and obstruct road extraction. Further, the occluded and shadow areas pose problem to the interpretability of orthophotos. This paper describes strategy of robust feature space analysis and multilevel thresholding adopted to extract shadow regions in ADS40 images automatically without the aid of Digital Surface models (DSM) or any other accessory data. In this work, low-level computer vision tasks for shadow extraction, elimination, and enhancement of texture information in the shadow regions in high-resolution ADS 40 digital aerial images were presented. A general nonparametric technique was implemented for the ADS 40 data points in the joint spatial- range domain for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The filtered image was segmented and then subjected to a bimodal thresholding to extract automatically shadow regions. Using an adaptive contrast enhancement approach, texture in the shadow regions was enhanced. All shadow regions caused by buildings, trees and other smaller objects in the urban areas were robustly extracted
