Textures and wavelet-domain joint statistics

TitleTextures and wavelet-domain joint statistics
Publication TypeConference Paper
Year of Publication2004
AuthorsAzimifar, Z., P. Fieguth, and E. Jernigan
Conference Name2004 International Conference on Image Analysis and Recognition
Conference LocationPortugal

This paper presents an empirical study of the joint wavelet statistics for textures and other random imagery. There is a growing realization that modeling wavelet coefficients as independent, or at best correlated only across scales, assuming independence within a scale, may be a poor assumption. While recent developments in wavelet-domain Hidden Markov Models (notably HMT-3S) account for within-scale dependencies, we find empirically that wavelet coefficients exhibit within- and across-subband neighborhood activities which are orientation dependent. Surprisingly these structures are not considered by the state-of-the-art wavelet modeling techniques. In this paper we describe possible choices of the wavelet statistical interactions by examining the joint-histograms, correlation coefficients, and the significance of coefficient relationships.