Comparison between adaptive search and bit allocation algorithms for image compression using vector quantization

Author

Liang, K.M. ; Huang, C.-M. ; Harris, R.W.

Author_Institution

Dept. of Electr. Eng., Utah State Univ., Logan, UT, USA

Volume

4

Issue

7

fYear

1995

fDate

7/1/1995 12:00:00 AM

Firstpage

1020

Lastpage

1023

Abstract

This article discusses bit allocation and adaptive search algorithms for mean-residual vector quantization (MRVQ) and multistage vector quantization (MSVQ). The adaptive search algorithm uses a buffer and a distortion threshold function to control the bit rate that is assigned to each input vector. It achieves a constant rate for the entire image but variable bit rate for each vector in the image. For a given codebook and several bit rates, we compare the performance between the optimal bit allocation and adaptive search algorithms. The results show that the performance of the adaptive search algorithm is only 0.20-0.53 dB worse than that of the optimal bit allocation algorithm, but the complexity of the adaptive search algorithm is much less than that of the optimal bit allocation algorithm

Keywords

adaptive signal processing; image coding; vector quantisation; MRVQ; MSVQ; adaptive search algorithm; bit rate control; buffer; codebook; constant bit rate; distortion threshold function; image compression; input vector; mean-residual vector quantization; multistage vector quantization; optimal bit allocation algorithm; performance; variable bit rate; Adaptive control; Bit rate; Computational complexity; Data compression; Discrete cosine transforms; Hardware; Image coding; Programmable control; Speech; Vector quantization;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.392343

Filename

392343