Context-based denoising of images using iterative wavelet thresholding

Detlev Marpe; Hans L. Cycon; Gunther Zander; Kai-Uwe Barthel

doi:10.1117/12.453135

4 January 2002 Context-based denoising of images using iterative wavelet thresholding

Detlev Marpe, Hans L. Cycon, Gunther Zander, Kai-Uwe Barthel

Proceedings Volume 4671, Visual Communications and Image Processing 2002; (2002) https://doi.org/10.1117/12.453135
Event: Electronic Imaging, 2002, San Jose, California, United States

Abstract

In this paper, we propose a spatially adaptive wavelet thresholding method using a context model that has been inspired by our prior work on image coding. The proposed context model relies on an estimation of the weighted variance in a local window of scale and space. Appropriately chosen weights are used to model the predominant correlations for a reliable statistical estimation. By iterating the context-based thresholding operation, a more accurate reconstruction can be achieved. Experimental results show that our proposed method yields significantly improved visual quality as well as lower mean squared error compared to the best recently published results in the denoising literature.

Citation Download Citation

Detlev Marpe, Hans L. Cycon, Gunther Zander, and Kai-Uwe Barthel "Context-based denoising of images using iterative wavelet thresholding", Proc. SPIE 4671, Visual Communications and Image Processing 2002, (4 January 2002); https://doi.org/10.1117/12.453135

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