학술논문

Comparison between adaptive search and bit allocation algorithms for image compression using vector quantization
Document Type
Periodical
Source
IEEE Transactions on Image Processing IEEE Trans. on Image Process. Image Processing, IEEE Transactions on. 4(7):1020-1023 Jul, 1995
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Computing and Processing
Bit rate
Image coding
Vector quantization
Computational complexity
Programmable control
Adaptive control
Hardware
Speech
Data compression
Discrete cosine transforms
Language
ISSN
1057-7149
1941-0042
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.ETX