Share Email Print

Proceedings Paper

Interpolative Adaptive Vector Quantization
Author(s): H. Sun; C, N. Manikopoulos
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Adaptive vector quantization with interpolation has been applied to the problem of edge degradation. An activity index A has been devised and used to classify the image into active and non-active regions according to the level of local detail. The non-active blocks were encoded by sampling and decoded by interpolation. Each active block was split into four smaller blocks which were coded by vector quantization. The number of samples extracted from each non-active block equals the size of the small blocks. So, each non-active block can be quantized with the same codebook. Thus, only one codebook was required. This greatly reduces the encoding and decoding computational effort. Computer simulation experiments have been carried out with an image of 256x256 pixels, 8 bit quantization and of medium detail level. The rate distortion curves obtained have shown that the adaptive interpolative encoding scheme outperforms alternative non-adaptive coding methods. Moreever, the edge information in the reconstructed image is well preserved . This was achieved at coding bit rates in the range of 0.8 to 1.0 bits per pixel.

Paper Details

Date Published: 18 July 1988
PDF: 4 pages
Proc. SPIE 0939, Hybrid Image and Signal Processing, (18 July 1988); doi: 10.1117/12.947050
Show Author Affiliations
H. Sun, Fairleigh Dickinson University (United States)
C, N. Manikopoulos, Fairleigh Dickinson University (United States)

Published in SPIE Proceedings Vol. 0939:
Hybrid Image and Signal Processing
David P. Casasent; Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top