Title :
Joint optimization of lattice vector quantizer and entropy coder for a Laplacian source
Author :
Kim, Won-Ha ; Hu, Yu-Hen ; Nguyen, Truong
Author_Institution :
Dept. of Electr. Eng., Wisconsin Univ., Madison, WI, USA
Abstract :
This paper presents a joint optimization algorithm for lattice vector quantization (LVQ) and entropy coding for a Laplacian source at all ranges of bit rates. Entropy-constrained lattice vector quantizers (ECLVQs) are often used in practical coding systems. In order to develop an ECLVQ design algorithm, we derive estimation expressions for both distortion and entropy. From these estimations, we develop an algorithm that jointly optimizes LVQ and the entropy coder pair for a given entropy rate. Compared to previously reported approaches, the approach reported quickly computes a highly accurate optimal ECLVQ at all ranges of bit rates. Since a Laplacian source represents a wide class of subband transformed data, the algorithm can be readily applied as a subband coding method. When the proposed algorithm is applied to a wavelet based image coding, the coding performance surpasses those of any previously reported subband coders, especially at low bit rates
Keywords :
codecs; encoding; entropy codes; signal processing; vector quantisation; Laplacian source; coding performance; coding systems; distortion; entropy coder; entropy coder pair; entropy coding; entropy rate; entropy-constrained lattice vector quantizers; joint optimization algorithm; lattice vector quantization; lattice vector quantizer; subband coders; subband coding method; subband transformed data; wavelet based image coding; Algorithm design and analysis; Bit rate; Books; Entropy coding; Image coding; Laplace equations; Lattices; Maximum likelihood estimation; Vector quantization; Yield estimation;
Conference_Titel :
Multimedia Signal Processing, 1997., IEEE First Workshop on
Conference_Location :
Princeton, NJ
Print_ISBN :
0-7803-3780-8
DOI :
10.1109/MMSP.1997.602622