30 May 2000 Regularized constrained restoration of wavelet-compressed image
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Proceedings Volume 4067, Visual Communications and Image Processing 2000; (2000) https://doi.org/10.1117/12.386629
Event: Visual Communications and Image Processing 2000, 2000, Perth, Australia
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.
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Junghoon Jung, Younhui Jang, Tae Yong Kim, Joon-Ki Paik, "Regularized constrained restoration of wavelet-compressed image", Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); doi: 10.1117/12.386629; https://doi.org/10.1117/12.386629
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