文章基本信息

标题：ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK
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作者：A. P. Dal Poz ; T. S. G. Mendes
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：2013
卷号：XL-1/W1
页码：53-56
DOI：10.5194/isprsarchives-XL-1-W1-53-2013
出版社：Copernicus Publications
摘要：This paper addresses the problem of road region detection in urban areas using an image classification approach. In order to minimize the spectral superposition of the road (asphalt) class with other classes, the Artificial Neural Networks (ANN) image classification method was used to classify geometrically-integrated high-resolution RGB aerial and laser-derived images. The RGB image was combined with different laser data layers and the ANN classification results showed that the radiometric and geometric laser data allows a better detection of road pixel
关键词：Artificial Neural Network; RGB Aerial Image; Normalized Digital Surface Model; Laser Pulse Intensity Image