Image denoising by directional averaging of wavelet coefficients

Bruno Huysmans; Alexandra Pižurica; Wilfried Philips

doi:10.1117/12.633996

7 November 2005 Image denoising by directional averaging of wavelet coefficients

Bruno Huysmans; Alexandra Pižurica; Wilfried Philips

Author Affiliations +

Proceedings Volume 6001, Wavelet Applications in Industrial Processing III; 60010E (2005) https://doi.org/10.1117/12.633996
Event: Optics East 2005, 2005, Boston, MA, United States

Abstract

In this paper a new denoising technique for gray valued images is presented. The proposed technique is best suited for flat or textured images affected by relatively low noise levels, where we aim at high quality reconstruction of tiny image structures and fine details. To avoid the attenuation of these fine image details, we replace the common wavelet thresholding and shrinking rules by an averaging step over a certain region of consistent edge directions. This region is obtained by first extracting the pixels that belong to an "oriented structure". We develop a classification algorithm which extracts the oriented structures by using directional information from the wavelet detail images. After this classification step we perform an adaptive averaging: each pixel is averaged over a window that depends on the detected structures in its neighbourhood. We demonstrate the visual improvement of our method over two spatially adaptive wavelet shrinkage methods.

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Bruno Huysmans, Bruno Huysmans, Alexandra Pižurica, Alexandra Pižurica, Wilfried Philips, Wilfried Philips, } "Image denoising by directional averaging of wavelet coefficients", Proc. SPIE 6001, Wavelet Applications in Industrial Processing III, 60010E (7 November 2005); doi: 10.1117/12.633996; https://doi.org/10.1117/12.633996

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