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A statistical unification of image interpolation, error concealment, and source-adapted filter design

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2 Author(s)
Muhlich, M. ; Image & Vision Group, Inst. for Appl. Phys., Frankfurt Am Main, Germany ; Mester, R.

The natural characteristics of image signals and the statistics of measurement noise are decisive for designing optimal filter sets and optimal estimation methods in signal processing. Astonishingly, this principle has so far only partially found its way into the field of image sequence processing. We show how a Wiener-type MMSE optimization criterion for the resulting image signal, based on a simple covariance model of images or image sequences, provides direct and intelligible solutions for various, apparently different, problems, such as error concealment, or adaption of filters to signal and noise statistics.

Published in:

Image Analysis and Interpretation, 2004. 6th IEEE Southwest Symposium on

Date of Conference:

28-30 March 2004