Title :
A statistical extension of normalized convolution and its usage for image interpolation and filtering
Author :
Muhlich, Matthias ; Mester, Rudolf
Author_Institution :
Inst. for Appl. Phys., J.W. Goethe-Univ. Frankfurt, Frankfurt am Main, Germany
Abstract :
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 solution for various, apparently different problems, such as error concealment, or adaption of filters to signal and noise statistics.
Keywords :
Wiener filters; convolution; filtering theory; image sequences; interpolation; least mean squares methods; optimisation; statistical analysis; Wiener-type MMSE optimization criterion; covariance image model; image filtering; image interpolation; image sequence processing; image signal characteristics; measurement noise; noise statistics; normalized convolution; optimal estimation methods; optimal filter set design; signal processing; statistical extension; Abstracts; Image edge detection; Information filters; Noise;
Conference_Titel :
Signal Processing Conference, 2004 12th European
Conference_Location :
Vienna
Print_ISBN :
978-320-0001-65-7
