Simulated annealing and codebook design

Abstract

A central issue in the use of vector quantization (VQ) for speech or image compression is the specification of the codebook. The traditional method for VQ codebook design is to use the Generalized Lloyd Algorithm (GLA), an iterative optimization procedure where an initial codebook is continually refined so that each iteration reduces the distortion involved in coding a given training set. However, this algorithm easily gets trapped in local minima of the distortion, resulting in a suboptimal codebook. Simulated Annealing (SA) is a procedure that employs randomness in a search algorithm and tends to skirt relatively poor local minima in favor of better ones. By altering the GLA with techniques motivated by SA we are able to improve the quality of the codebwks by reducing the distortion involved in coding the training set. Results are presented in the context of image coding using VQ.

Efficient vector quantization using genetic algorithm

“…Many algorithms for optimal codebook design have been proposed [6,[11][12][13][14][15][16][17]. Among them, the most popular one was developed by Linde et al [6] and is referred to as the LBG algorithm.…”

A Direct Method for Semantic Partitioning of Low-level Image Data

“…There are several codebook design algorithms at the moment, such as the LBG algorithm [6] , the pairwise nearest neighbor algorithm(PNNA) [7] , the simulated annealing algorithm(SAA) [8] and the gentic algorithm(GA) [9] , etc. But the codebook design processs of these algorithms is performed on vector whose components are prone to interfere one another, which may blur the latent semantics of data and lead to slow speed.…”

Fast Search Algorithms for VQ Codebook Generation

“…This method a number of years for data compression. With its relatively usually needs a very large number of additional computasimple structure and computation, VQ has received great tions and obtains a small amount of distortion imattention in the last decade [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Many types of VQ, such provement.…”

“…To solve this problem, the Simulated AnVector quantization (VQ) techniques have been used for nealing (SA) method may be used [16,17]. This method a number of years for data compression.…”