@inproceedings {756,
	title = {Textures and wavelet-domain joint statistics},
	booktitle = {2004 International Conference on Image Analysis and Recognition},
	year = {2004},
	address = {Portugal},
	abstract = {<p>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.</p>
},
	doi = {http://dx.doi.org/10.1007/978-3-540-30126-4_41},
	author = {Z Azimifar and P Fieguth and E Jernigan}
}
