Open Access

Locally Adaptive DCT Filtering for Signal-Dependent Noise Removal

  • Ruşen Öktem1Email author,
  • Karen Egiazarian2,
  • Vladimir V. Lukin3,
  • Nikolay N. Ponomarenko3 and
  • Oleg V. Tsymbal4
EURASIP Journal on Advances in Signal Processing20072007:042472

https://doi.org/10.1155/2007/42472

Received: 13 October 2006

Accepted: 13 May 2007

Published: 27 June 2007

Abstract

This work addresses the problem of signal-dependent noise removal in images. An adaptive nonlinear filtering approach in the orthogonal transform domain is proposed and analyzed for several typical noise environments in the DCT domain. Being applied locally, that is, within a window of small support, DCT is expected to approximate the Karhunen-Loeve decorrelating transform, which enables effective suppression of noise components. The detail preservation ability of the filter allowing not to destroy any useful content in images is especially emphasized and considered. A local adaptive DCT filtering for the two cases, when signal-dependent noise can be and cannot be mapped into additive uncorrelated noise with homomorphic transform, is formulated. Although the main issue is signal-dependent and pure multiplicative noise, the proposed filtering approach is also found to be competing with the state-of-the-art methods on pure additive noise corrupted images.

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Authors’ Affiliations

(1)
Electrical and Electronics Engineering Department, Atılım University
(2)
Institute of Signal Processing, Tampere University of Technology
(3)
Department of Receivers, Transmitters and Signal Processing, National Aerospace University
(4)
Kalmykov Center for Radiophysical Sensing of Earth

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Copyright

© Ruşen Öktem et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.