Lattice vector quantization with reduced or without look-up table
Patrick Rault, Christine M. Guillemot · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
This paper describes a new vector indexing algorithm for Lattice Vector Quantization (LVQ). The technique applies to a large class of lattices such as Zn, An, Dn, or E8, widely used in signal compression. Relying on a partitioning of the events sources, based on a notion of leaders as proposed, it allows to trade vector look-up table size for arithmetic operations. At the cost of a very small number of integer arithmetic operations, The algorithm leads to a very significant reduction of the vector look-up tables. This in turn leads to reduced encoder and decoder complexities. The introduction of the concept of 'absolute' leaders, and of the corresponding coding and decoding algorithms, provides additional flexibility in trading table size for arithmetic operations. The association of these vector indexing techniques with product codes, in the framework of LVQ, leads to increased compression performances.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.