Automatic extraction of building in a dense urban area from very high resolution satellite images
Publish place: 5th Symposium on Advances in Science and Technology
Publish Year: 1390
Type: Conference paper
Language: English
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Document National Code:
SASTECH05_234
Index date: 12 August 2012
Automatic extraction of building in a dense urban area from very high resolution satellite images abstract
An inclusive accessibility of very high resolution (VHR) satellite images has generated more interest in automatic extraction of buildings for some practical applications such as updating geographic information system (GIS) database, land management, cadastre, and 3D city modeling. Extraction of buildings especially in a dense urban area containing many different and connected parts is an intricate problem due to a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as a variety of difficulties such as shadows and similar spectra. In order to face this problem properly, we present an algorithm for extraction and improvement of buildings. The process consists of four steps: (1) separate building and non-building pixels, (2) improve the building layer, and (3) segment pixels that belong to the building layer. The proposed algorithm is evaluated for a case study in Tehran, Islamic Republic of Iran using a pan sharpened multispectral GeoEye satellite image. The experiments show that the algorithm extracts 78.3 % of buildings with a quality percentage 59.7 % in a dense urban area
Automatic extraction of building in a dense urban area from very high resolution satellite images Keywords:
Building Extraction , Very High Resolution (VHR) Satellite Images , Dense Urban Area , K-means Clustering , Region Growing
Automatic extraction of building in a dense urban area from very high resolution satellite images authors
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