An efficient adaptive arithmetic coding for block-based lossless image compression using mixture models

Atef Masmoudi 1 Afif Masmoudi 1 William Puech 2
2 ICAR - Image & Interaction
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : In this paper, we investigate finite mixture models (FMM) and adaptive arithmetic coding (AAC) for block-based lossless image compression. The AAC performance depends on how well the model fits the source symbols' statistics. In addition, when encoding small block, the number of source symbols is considerably large by comparison with the number of samples in that block, which results in a loss of compression efficiency. To this end, we propose to model each block with an appropriately FMM by maximizing the probability of samples that belong to that block. The mixture parameters are estimated through maximum likelihood using the Expectation-Maximization (EM) algorithm in order to maximize the arithmetic coding efficiency. The comparative studies of some particular test images prove the efficiency of the mixture models for lossless image compression. The experimental results show significant improvements over conventional adaptive arithmetic encoders and the state-of-the-art lossless image compression standards and algorithms.
Type de document :
Communication dans un congrès
ICIP: International Conference on Image Processing, Oct 2014, Paris, France. 21st IEEE International Conference on Image Processing, pp.5646-5650, 2014, 〈https://icip2014.wp.mines-telecom.fr〉. 〈10.1109/ICIP.2014.7026142〉
Liste complète des métadonnées

https://hal-lirmm.ccsd.cnrs.fr/lirmm-01379586
Contributeur : William Puech <>
Soumis le : mardi 11 octobre 2016 - 17:14:52
Dernière modification le : jeudi 24 mai 2018 - 15:59:23

Identifiants

Collections

Citation

Atef Masmoudi, Afif Masmoudi, William Puech. An efficient adaptive arithmetic coding for block-based lossless image compression using mixture models. ICIP: International Conference on Image Processing, Oct 2014, Paris, France. 21st IEEE International Conference on Image Processing, pp.5646-5650, 2014, 〈https://icip2014.wp.mines-telecom.fr〉. 〈10.1109/ICIP.2014.7026142〉. 〈lirmm-01379586〉

Partager

Métriques

Consultations de la notice

105