<title>Multiresolution sequential image change detection with wavelets</title>

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.