Zohar Feldman, Avishai Mandelbaum
WSC 2010
Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's 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. © 1996 IEEE.
Zohar Feldman, Avishai Mandelbaum
WSC 2010
Hang-Yip Liu, Steffen Schulze, et al.
Proceedings of SPIE - The International Society for Optical Engineering
Raymond F. Boyce, Donald D. Chamberlin, et al.
CACM
Corneliu Constantinescu
SPIE Optical Engineering + Applications 2009