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Proceedings Paper

Regularized constrained restoration of wavelet-compressed image
Author(s): Junghoon Jung; Younhui Jang; Tae Yong Kim; Joon-Ki Paik
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Paper Abstract

Wavelet-compressed images suffer from coding artifacts, such as ringing and blurring, resulted from the quantization of transform coefficients. In this paper we propose a new algorithm that reduces such coding artifacts in wavelet- compressed images by using regularized iterative image restoration. We, first, propose an appropriate model for the image degradation system which represents the wavelet-based image compression system. Then the model is used to formulate the regularized iterative restoration algorithm. The proposed algorithm adopts a couple of constraints, and adaptivity is imposed to the general regularization process on both spatial and frequency domain. Experimental results show that the solution of the proposed iteration converges to the image in which both ringing and blurring are significantly reduced.

Paper Details

Date Published: 30 May 2000
PDF: 8 pages
Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); doi: 10.1117/12.386629
Show Author Affiliations
Junghoon Jung, Chung-Ang Univ. (South Korea)
Younhui Jang, Chung-Ang Univ. (South Korea)
Tae Yong Kim, Chung-Ang Univ. (South Korea)
Joon-Ki Paik, Chung-Ang Univ. (South Korea)

Published in SPIE Proceedings Vol. 4067:
Visual Communications and Image Processing 2000
King N. Ngan; Thomas Sikora; Ming-Ting Sun, Editor(s)

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