Share Email Print

Proceedings Paper

WCRP: a software development system for efficient wavelet-based image codec design
Author(s): Yiliang Bao; Houng-Jyh Mike Wang; C.-C. Jay Kuo
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A wavelet-based image codec compresses an image with three major steps: discrete wavelet transform, quantization and entropy coding. There are many variants in each step. In this research, we consider a versatile software development system called the wavelet compression research platform (WCRP). WCRP provides a framework to host components of all compression steps. For each compression stage, multiple components are developed and they are contained in WCRP. They include a selection of floating-point and integer filter sets, different transform strategies, a set of quantizers and two different arithmetic coders. A codec can be easily formed by picking up components in different stages. WCRP provides an excellent tool to test the performance of various image codec designs. In addition, WCRP is an extensible system, i.e., new components available in the future can be easily incorporated and quickly tested. It makes the development of new algorithms much easier. WCRP has been used in developing a family of new quantization algorithms that are based on the concept of Binary Description of multi-level wavelet coding objects. These quantization schemes can serve different applications, such as progressive fidelity coding, lossless coding and low complexity coding. Both progressive fidelity coding and lossless coding performance of our codec are among the best in its class. A codec of low implementational complexity is made possible by our memory-scalable quantization scheme.

Paper Details

Date Published: 1 October 1998
PDF: 10 pages
Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); doi: 10.1117/12.323205
Show Author Affiliations
Yiliang Bao, Univ. of Southern California (United States)
Houng-Jyh Mike Wang, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 3460:
Applications of Digital Image Processing XXI
Andrew G. Tescher, 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?