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Title: Coding with partially hidden Markov models
Type: Article in proceedingsArticle in proceedings
Participant(s):
Author:  Forchhammer, Søren (Cwisno: 575)
Technical University of Denmark
Email:

Forfatter:  Rissanen, J.
Technical University of Denmark

Abstract: Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given. The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt to instationarities in the images
Published: part of: Proceedings of Data Compression Conference (ISBN: 08-18-67012-6), pages: 92-101, 1995, IEEE,
DOI:
File(s):
Presented at: Data Compression Conference 1995, Snowbird, UT
See the publication in DTU Orbit See the publication in DTU Orbit

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