DocumentCode
1087725
Title
Partially hidden Markov models
Author
Forchhammer, Soren ; Rissanen, Jorma
Author_Institution
Inst. of Telecommun., Tech. Univ., Lyngby, Denmark
Volume
42
Issue
4
fYear
1996
fDate
7/1/1996 12:00:00 AM
Firstpage
1253
Lastpage
1256
Abstract
Partially hidden Markov models (PHMM) are introduced. They differ from the ordinary HMMs in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where the hidden variables may be interpreted as representing noncausal pixels
Keywords
data compression; hidden Markov models; image coding; image representation; probability; black and white image compression; hidden states; noncausal pixels; output probabilities; partially hidden Markov models; past observations; transition probabilities; Councils; Data compression; Hidden Markov models; Image coding; Parameter estimation; Pixel; Probability distribution; Speech recognition; State-space methods; Text recognition;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.508852
Filename
508852
Link To Document