Vector Quantization by Packing of Embedded Truncated Lattices

Vincent Ricordel (1) , Claude Labit (1)

1 TEMIS - Advanced Image Sequence Processing

The purpose of this paper is to introduce a new vector quantizer (VQ) for the compression of digital image sequences. Our approach unifies both efficient coding methods: a fast lattice encoding and an unbalanced tree-structured codebook design according to a distortion vs. rate tradeoff. This tree-structured lattice VQ (TSLVQ) is based on the hierarchical packing of embedded truncated lattices. So we investigate the design of the hierarchical set of truncated lattice structures which can be optimally embedded. We present the simple quantization procedure and describe the corresponding tree-structured codebook. Finally two unbalanced tree-structured codebook design algorithms based on the BFOS distortion vs. rate criterion are used.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Vincent Ricordel, Claude Labit. Vector Quantization by Packing of Embedded Truncated Lattices. IEEE International Conference on Image Processing (ICIP), Oct 1995, Washington DC, United States. ⟨10.1109/ICIP.1995.538545⟩. ⟨hal-00451365⟩