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Proceedings Paper

Improvement of building extraction using decision fusion of locally and globally enhanced IKONOS images
Author(s): Seyed Mostafa Mirhassani; Bardia Yousefi; Mitra Bahadorian; Heydar Toossian Shandiz
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Paper Abstract

In this paper a fully automated algorithm for building extraction from remote sensing IKONOS images is presented. Local and global enhancement of an original image improves the rate of building detection in some cases. However, some undesirable effects could occur due to image enhancement. As a result the Bayesian classification method which has been previously used could result in errors. To deal with such problems, decision fusion is used together with a shadow-based verification step to achieve a better result from locally and globally enhanced classified images. Experimental results justify the efficiency of the proposed method in dealing with the problem of building extraction in IKONOS images.

Paper Details

Date Published: 17 November 2008
PDF: 10 pages
Proc. SPIE 7266, Optomechatronic Technologies 2008, 72661I (17 November 2008); doi: 10.1117/12.807592
Show Author Affiliations
Seyed Mostafa Mirhassani, Islamic Azad Univ. (Iran, Islamic Republic of)
Bardia Yousefi, Shahrood Univ. of Technology (Iran, Islamic Republic of)
Mitra Bahadorian, KTH-Royal Institute of Technology (Sweden)
Heydar Toossian Shandiz, Shahrood Univ. of Technology (Iran, Islamic Republic of)

Published in SPIE Proceedings Vol. 7266:
Optomechatronic Technologies 2008
John T. Wen; Dalibor Hodko; Yukitoshi Otani; Jonathan Kofman; Okyay Kaynak, Editor(s)

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