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Proceedings Paper

Study on the capabilities of morphological attribute profiles in change detection on VHR images
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Paper Abstract

The analysis of changes occurred in multi-temporal images acquired by the same sensor on the same geographical area at different dates is usually done by performing a comparison of the two images after co-registration. When one considers very high resolution (VHR) remote sensing images, the spatial information of the pixels becomes very important and should be included in the analysis. However, taking into account spatial features for change detection in VHR images is far from being straightforward, due to effects such as seasonal variations, differences in illumination condition, residual mis-registration, different acquisition angles, etc., which make the comparison of the structures in the scene complex to achieve from a spatial perspective. In this paper we propose a change detection technique based on morphological Attribute Profiles (APs) suitable for the analysis of VHR images. In greater detail, this work aims at detecting the changes occurred on the ground between the two acquisitions by comparing the APs computed on the image of each date. The experimental analysis has been carried out on two VHR multi-temporal images acquired by the Quickbird sensor on the city of Bam, Iran, before and after the earthquake occurred on Dec. 26, 2003. The experiments confirm that the APs computed at different dates show different behaviors for changed and unchanged areas. The change detection maps obtained by the proposed technique are able to detect changes in the morphology of the correspondent regions at different dates regardless their spectral variations.

Paper Details

Date Published: 22 October 2010
PDF: 10 pages
Proc. SPIE 7830, Image and Signal Processing for Remote Sensing XVI, 783016 (22 October 2010); doi: 10.1117/12.866178
Show Author Affiliations
Nicola Falco, Univ. degli Studi di Trento (Italy)
Mauro Dalla Mura, Univ. degli Studi di Trento (Italy)
Univ. of Iceland (Iceland)
Francesca Bovolo, Univ. degli Studi di Trento (Italy)
Jon Atli Benediktsson, Univ. of Iceland (Iceland)
Lorenzo Bruzzone, Univ. degli Studi di Trento (Italy)

Published in SPIE Proceedings Vol. 7830:
Image and Signal Processing for Remote Sensing XVI
Lorenzo Bruzzone, Editor(s)

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