TY - GEN
T1 - Bayes Code for 2-dimensional auto-regressive Hidden Markov model and its application to lossless image compression
AU - Nakahara, Yuta
AU - Matsushima, Toshiyasu
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Numbers JP17K00316, JP17K06446, JP18K11585, and 19K04914.
Publisher Copyright:
© 2020 SPIE.
PY - 2020
Y1 - 2020
N2 - For general lossless data compression in information theory, researchers have repeated expansion of stochastic models to express target data and design of codes for the expanded models. In this paper, we apply this approach to lossless image compression. We expand an auto-regressive hidden Markov model to a 2-dimensional model to express images containing single diagonal edge. Then, we design a Bayes code with an approximative parameter estimation by variational Bayesian methods. Experimental results for synthetic images show that the proposed model is sufficiently flexible for the target images and the parameter estimation is accurate enough. We also confirm the behavior of the proposed method on real images.
AB - For general lossless data compression in information theory, researchers have repeated expansion of stochastic models to express target data and design of codes for the expanded models. In this paper, we apply this approach to lossless image compression. We expand an auto-regressive hidden Markov model to a 2-dimensional model to express images containing single diagonal edge. Then, we design a Bayes code with an approximative parameter estimation by variational Bayesian methods. Experimental results for synthetic images show that the proposed model is sufficiently flexible for the target images and the parameter estimation is accurate enough. We also confirm the behavior of the proposed method on real images.
KW - Auto-regressive hidden Markov model
KW - Bayes code
KW - Generative model
KW - Lossless image compression
KW - Variational Bayesian methods
UR - http://www.scopus.com/inward/record.url?scp=85086639019&partnerID=8YFLogxK
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U2 - 10.1117/12.2566943
DO - 10.1117/12.2566943
M3 - Conference contribution
AN - SCOPUS:85086639019
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - International Workshop on Advanced Imaging Technology, IWAIT 2020
A2 - Lau, Phooi Yee
A2 - Shobri, Mohammad
PB - SPIE
T2 - International Workshop on Advanced Imaging Technology, IWAIT 2020
Y2 - 5 January 2020 through 7 January 2020
ER -