28 December 1998 Low-complexity postprocessing of wavelet-coded images via robust estimation and nonlinear filtering
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Proceedings Volume 3653, Visual Communications and Image Processing '99; (1998); doi: 10.1117/12.334615
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
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.
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Mei-Yin Shen, C.-C. Jay Kuo, "Low-complexity postprocessing of wavelet-coded images via robust estimation and nonlinear filtering", Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334615; https://doi.org/10.1117/12.334615
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KEYWORDS
Nonlinear filtering

Image compression

Data modeling

Wavelets

Distortion

Image analysis

Quantization

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