Improvement of building extraction using decision fusion of locally and globally enhanced IKONOS images

Seyed Mostafa Mirhassani; Bardia Yousefi; Mitra Bahadorian; Heydar Toossian Shandiz

doi:10.1117/12.807592

17 November 2008 Improvement of building extraction using decision fusion of locally and globally enhanced IKONOS images

Seyed Mostafa Mirhassani, Bardia Yousefi, Mitra Bahadorian, Heydar Toossian Shandiz

Author Affiliations +

Proceedings Volume 7266, Optomechatronic Technologies 2008; 72661I (2008) https://doi.org/10.1117/12.807592
Event: International Symposium on Optomechatronic Technologies, 2008, San Diego, California, United States

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.

Citation Download Citation

Seyed Mostafa Mirhassani, Bardia Yousefi, Mitra Bahadorian, and Heydar Toossian Shandiz "Improvement of building extraction using decision fusion of locally and globally enhanced IKONOS images", Proc. SPIE 7266, Optomechatronic Technologies 2008, 72661I (17 November 2008); https://doi.org/10.1117/12.807592

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