Share Email Print
cover

Proceedings Paper

Low-complexity postprocessing of wavelet-coded images via robust estimation and nonlinear filtering
Author(s): Mei-Yin Shen; C.-C. Jay Kuo
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

A postprocessing algorithm for compression artifact reduction in low-bit-rate wavelet coding is proposed in this work. We first formulate the artifact reduction problem as a robust estimation problem. Under this framework, the artifact-free image is obtained by minimizing a cost function that accounts for the smoothness constraint as well as image fidelity. To compute the estimate, computationally intensive algorithms such as simulated annealing and gradient descent search are often adopted. To reduce the computational complexity, a nonlinear filtering technique is proposed in this work to find the approximate global minimum with a lower computational cost. We have performed our experiments on images coded by JPEG-2000 standard and observed the proposed method is effective in reducing the severe ringing artifact while maintaining low complexity and low memory bandwidth.

Paper Details

Date Published: 28 December 1998
PDF: 12 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334615
Show Author Affiliations
Mei-Yin Shen, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

© SPIE. Terms of Use
Back to Top