@inproceedings{3e6ed58ca6c64d19acf7dbcfd9b67548,
title = "Analysis of multiscale texture segmentation using wavelet-domain hidden Markov models",
abstract = "Wavelet-domain hidden Markov tree (HMT) models are powerful tools for modeling the statistical properties of wavelet transforms. By characterizing the joint statistics of the wavelet coefficients, HMTs efficiently capture the characteristics of a large class of real-world signals and images. In this paper, we apply this multiscale statistical description to the texture segmentation problem. We also show how the Kullback-Leibler (KL) distance between texture models can provide a simple performance indicator.",
author = "Hyeokho Choi and Brent Hendricks and Richard Baraniuk",
note = "Publisher Copyright: {\textcopyright} 1999 IEEE.; 33rd Asilomar Conference on Signals, Systems, and Computers, ACSSC 1999 ; Conference date: 24-10-1999 Through 27-10-1999",
year = "1999",
doi = "10.1109/ACSSC.1999.831914",
language = "English (US)",
series = "Conference Record of the 33rd Asilomar Conference on Signals, Systems, and Computers",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1287--1291",
editor = "Matthews, {Michael B.}",
booktitle = "Conference Record of the 33rd Asilomar Conference on Signals, Systems, and Computers",
address = "United States",
}