Low complexity bit allocation based on a multidimensional mixture model using lattice vector quantization - Archive ouverte HAL
Communication Dans Un Congrès Année : 2012

Low complexity bit allocation based on a multidimensional mixture model using lattice vector quantization

Résumé

We present a low computational cost bit allocation procedure dedicated to wavelet compression performed by entropy coded lattice vector quantization (ECLVQ). It is based on a previously proposed statistical model called multidimensional mixture of generalized Gaussian densities. Here, we focus on the distribution estimation step which requires to be as fast as possible. We show that the method of moments can be used successfully as an alternative to Monte Carlo Markov chain approach (MCMC) ; this method allows not only to reduce the computational complexity but also to maintain a good estimation performance. Experimental results show the efficiency of our approach in terms of CPU time.
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Dates et versions

hal-00691593 , version 1 (26-04-2012)

Identifiants

  • HAL Id : hal-00691593 , version 1

Citer

Yann Gaudeau, Ludovic Guillemot, Saïd Moussaoui, Jean-Marie Moureaux. Low complexity bit allocation based on a multidimensional mixture model using lattice vector quantization. Picture Coding Symposium 2012, PCS'2012, May 2012, Cracovie, Poland. pp.CDROM. ⟨hal-00691593⟩
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