New likelihood test methods for change detection in image sequences

Modeling the image as a piecewise linear gray-value function of the pixel coordinates considerably improved a change detection test based previously on a piecewise constant gray-value function. These results encouraged investigations into modeling the picture as a mosaic of patches where the gray-va...

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Bibliographic Details
Published in:Computer vision, graphics, and image processing graphics, and image processing, 1984-01, Vol.26 (1), p.73-106
Main Authors: Hsu, Y.Z, Nagel, H.-H, Rekers, G
Format: Article
Language:English
Subjects:
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Imaging and optical processing
Optics
Physics
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Summary:Modeling the image as a piecewise linear gray-value function of the pixel coordinates considerably improved a change detection test based previously on a piecewise constant gray-value function. These results encouraged investigations into modeling the picture as a mosaic of patches where the gray-value function within each patch is described as a second-order bivariate polynomial of the pixel coordinates. Such a more appropriate model allowed the assumption to be made that the remaining gray-value variation within each patch can be attributed to noise related to the sensing and digitizing devices, independent of the individual image frames in a sequence. This assumption made it possible to relate the likelihood test for change detection to well-known statistical tests ( t test, F test), facilitating the determination of threshold values related to a priori confidence limits.
ISSN:0734-189X
1557-895X
DOI:10.1016/0734-189X(84)90131-2