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Proceedings Paper

Multiresolution sequential image change detection with wavelets
Author(s): Yawgeng A. Chau; Jar-Chi Shee
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Paper Abstract

Multiresolution image change detection based on the wavelet expansion is addressed. The multiresolution change detection is modeled as a sequential hypothesis test problem. A modified multistage truncated sequential probability ratio test (TSPRT) is developed for the change detection problem. With the multistage TSPRT, the devised scheme for change detection employs multiresolution images with increasing sample sizes. The maximum likelihood (ML) estimation is used to obtain the mean, variance, and the relevant correlation coefficients of the image signals for the test. To determine the thresholds of the TSPRT, a suboptimal technique in accordance with the constant false alarm and missing probabilities for the hypothesis test problem is considered. To illustrate the performance of the developed multiresolution change detection scheme, experimental results are presented. From the experimental results, it is asserted that the developed multiresolution change detection algorithm can accurately disclose the changing areas in a consecutive image sequence.

Paper Details

Date Published: 27 February 1996
PDF: 10 pages
Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); doi: 10.1117/12.233265
Show Author Affiliations
Yawgeng A. Chau, Yuan-Ze Institute of Technology (Taiwan)
Jar-Chi Shee, Yuan-Ze Institute of Technology (Taiwan)


Published in SPIE Proceedings Vol. 2727:
Visual Communications and Image Processing '96
Rashid Ansari; Mark J. T. Smith, Editor(s)

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