Image compression using the Iteration-Tuned and Aligned Dictionary

Joaquin Zepeda 1, 2 Christine Guillemot 1 Ewa Kijak 2
1 TEMICS - Digital image processing, modeling and communication
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
2 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the Iteration-Tuned and Aligned Dictionary (ITAD). The question of selecting the number of atoms used in the representation of each image block is addressed with a new, global (image-wide), rate-distorition-based sparsity selection criterion. We show experimentally that our codec outperforms JPEG2000 in both quantitative evaluations (by 0.9 dB to 4 dB) and qualitative evaluations.
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https://hal.archives-ouvertes.fr/hal-00647253
Contributor : Ewa Kijak <>
Submitted on : Thursday, December 1, 2011 - 5:11:39 PM
Last modification on : Friday, November 16, 2018 - 1:21:55 AM

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Joaquin Zepeda, Christine Guillemot, Ewa Kijak. Image compression using the Iteration-Tuned and Aligned Dictionary. IEEE International Conference on Acoustics, Speech and Signal Processing, May 2011, Czech Republic. pp.793 - 796, ⟨10.1109/ICASSP.2011.5946523⟩. ⟨hal-00647253⟩

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