Changes Detection in Two Images Using Walsh Functions and the Likelihood Test Method
The gray-value function in a local window is approximated by a series of the Walsh functions. Several terms of this series adequately model the gray-value function in the window, and the remaining variability can be attributed to noise. When comparing two images, one finds the coefficients of the Walsh functions for each consecutive position of the window in both images. Detection of the change between the corresponding windows is based on the maximum likelihood ratio testing, which consists in deciding between two hypotheses: Ho - there is no motion, versus H1 - there is motion. The results of change detection are presented for images of a natural scene, obtained by means of the CCD camera, as well as for simulated images subjected to the influence of Gaussian noise. The computer program described carries out the F-test for the maximum likelihood ratio. It is shown that such a program can be successfully used for change detection in image sequences.
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