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Proceedings Paper

Change detection method for remotely sensed images based on multivariate analysis method and statistical test
Author(s): Hiroshi Okumura; Ryohei Yamasaki; Tatsunori Goto; Kohei Arai
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Paper Abstract

A new change detection method for remotely sensed images is proposed. This method can be applied to two images which have different number of spectral bands and/or have different spectral ranges. The proposed method converts two multi-spectral-multi-temporal images into two sets of canonical variate images which have limited correlation called the canonical correlation. Then, one or more canonical variate images which are the most suitable for change detection are selected and change detection regions in the original images are extracted by using statistical modeling and statistical test. In this paper, the detail of the proposed method is described. Some experiments using simulated multi-spectral-multi-temporal images based on spectral profiles in ASTER Spectral Library are conducted to confirm change detection accuracy. The experimental results show reasonable changed regions and their change quantities.

Paper Details

Date Published: 28 September 2009
PDF: 8 pages
Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 747717 (28 September 2009); doi: 10.1117/12.830329
Show Author Affiliations
Hiroshi Okumura, Saga Univ. (Japan)
Ryohei Yamasaki, Saga Univ. (Japan)
Tatsunori Goto, Saga Univ. (Japan)
Kohei Arai, Saga Univ. (Japan)


Published in SPIE Proceedings Vol. 7477:
Image and Signal Processing for Remote Sensing XV
Lorenzo Bruzzone; Claudia Notarnicola; Francesco Posa, Editor(s)

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