Empirical evaluation of dissimilarity measures for use in urban structural damage detection

ZhiQiang Chen; Tara C. Hutchinson

doi:10.1117/12.704553

28 February 2007 Empirical evaluation of dissimilarity measures for use in urban structural damage detection

ZhiQiang Chen, Tara C. Hutchinson

Proceedings Volume 6498, Computational Imaging V; 64981F (2007) https://doi.org/10.1117/12.704553
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

Abstract

Multi-temporal earth-observation imagery is now available at sub-meter accuracy and has been found very useful for performing quick damage detection for urban areas affected by large-scale disasters. The detection of structural damage using images taken before and after disaster events is usually modeled as a change detection problem. In this paper, we propose a new perspective for performing change detection, where dissimilarity measures are used to extract urban structural damage. First, image gradient magnitudes and spatial variances are used as a means to capture urban structural features. Subsequently, a family of distribution dissimilarity measures, including: Euclidean distance, Cosine, Jeffery divergence, and Bhattacharyya distance, are used to extract structural damage. We particularly focus on evaluating the performance of these dissimilarity-based change detection methods under the framework of pattern classification and crossvalidation, and with the use of a pair of bi-temporal satellite images captured before and after a major earthquake in Bam, Iran. The paper concludes that the proposed change detection methods for urban structural damage detection, which are conceptually simple and computationally efficient, outperform the traditional correlation analysis in terms of both classification accuracy and tolerance to local alignment errors.

Citation Download Citation

ZhiQiang Chen and Tara C. Hutchinson "Empirical evaluation of dissimilarity measures for use in urban structural damage detection", Proc. SPIE 6498, Computational Imaging V, 64981F (28 February 2007); https://doi.org/10.1117/12.704553

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available