JOURNAL ARTICLE

Image Compression Using Adaptive Vector Quantization

M. GoldbergPaul BoucherSeymour Shlien

Year: 1986 Journal:   IRE Transactions on Communications Systems Vol: 34 (2)Pages: 180-187   Publisher: Institute of Electrical and Electronics Engineers

Abstract

The paper demonstrates the application of adaptive vector quantization techniques to the coding of monochromatic and color pictures. Codebooks of representative vectors are generated for different portions of the image. By means of extensive simulations, the performance of the coder for monochrome images is estimated as a function of the various coding parameters-vector dimensionality, number of representative vectors, and degree of adaptivity. It is shown that for a vector size of dimension 4, there is a zone of operation, ranging from 1.0 to 1.5 bits/pixel, where adaptive vector quantization is advantageous. Despite the simplicity of the decoder, the performance of the adaptive vector quantizer is found to be comparable with block transform coding schemes for both monochrome and color pictures.

Keywords:
Vector quantization Monochrome Artificial intelligence Linde–Buzo–Gray algorithm Computer science Pixel Image compression Pattern recognition (psychology) Color quantization Quantization (signal processing) Computer vision Mathematics Algorithm Color image Image (mathematics) Image processing

Metrics

110
Cited By
4.78
FWCI (Field Weighted Citation Impact)
29
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Digital Filter Design and Implementation
Physical Sciences →  Computer Science →  Signal Processing

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