Share Email Print

Proceedings Paper

Applications Of Vector Quantization To Progressive Compression And Transmission Of Images
Author(s): M. Ibrahim Sezan; Chia-Lung Yeh; A. Murat Tekalp; Majid Rabbani; Paul Jones
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In this paper, we develop a technique based on tree-searched mean residual vector quantization (MRVQ) for progressive compression and transmission of images. In the first stage, averages over image subblocks of a certain size are transmitted. If the receiver decides to retain the image, the residual image generated by subtracting the block averages from the original is progressively transmitted using the tree-searched vector quantization (VQ) hierarchy. In an attempt to reduce the bit-rate of the initial transmission, Knowlton's scheme is used to transmit the block averages progressively. Using a (4x4) block size, we obtain high quality images at 1.4 bits/pixel.

Paper Details

Date Published: 13 October 1987
PDF: 5 pages
Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); doi: 10.1117/12.976483
Show Author Affiliations
M. Ibrahim Sezan, Eastman Kodak Company (United States)
Chia-Lung Yeh, NYNEX Corporation (United States)
A. Murat Tekalp, University of Rochester (United States)
Majid Rabbani, Eastman Kodak Company (United States)
Paul Jones, Eastman Kodak Company (United States)

Published in SPIE Proceedings Vol. 0845:
Visual Communications and Image Processing II
T. Russell Hsing, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?