Image denoising using fractal- and wavelet-based methods

Kai Uwe Barthel; Hans L. Cycon; Detlev Marpe

doi:10.1117/12.516206

27 February 2004 Image denoising using fractal- and wavelet-based methods

Kai Uwe Barthel, Hans L. Cycon, Detlev Marpe

Proceedings Volume 5266, Wavelet Applications in Industrial Processing; (2004) https://doi.org/10.1117/12.516206
Event: Photonics Technologies for Robotics, Automation, and Manufacturing, 2003, Providence, RI, United States

Abstract

There is a considerable amount of literature about image denoising using wavelet-based methods. Some new ideas where also reported using fractal methods. In this paper we propose a hybrid wavelet-fractal denoising method. Using a non-subsampled overcomplete wavelet transform we present the image as a collection of translation invariant copies in different frequency subbands. Within this multiple representation we do a fractal coding which tries to approximate a noise free image. The inverse wavelet transform of the fractal collage leads to the denoised image. Our results are comparable to some of the most efficient known denoising methods.

Citation Download Citation

Kai Uwe Barthel, Hans L. Cycon, and Detlev Marpe "Image denoising using fractal- and wavelet-based methods", Proc. SPIE 5266, Wavelet Applications in Industrial Processing, (27 February 2004); https://doi.org/10.1117/12.516206

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