IMPROVED BM3D FOR CORRELATED NOISE REMOVAL

Marcella Matrecano, Giovanni Poggi, Luisa Verdoliva

Abstract

Most of the literature on denoising focuses on the additive-white-gaussian-noise (AWGN) model. However, in many important applicative fields, images are typically affected by non-Gaussian and/or colored noise, in which cases AWGN-based techniques fall much short of their promises. In this paper, we propose a new denoising technique for correlated noise based on the non-local approach. We start from the well-known BM3D algorithm, which can be considered to be the state of the art in AWGN denoising, and modify it in various critical steps in order to take into account the non-whiteness of noise. Experimental results on several test images corrupted by correlated noise confirm the potential of the proposed technique.

References

  1. Buades, A., Coll, B. and Morel, J. M., (2005). A Review of Image Denoising Algorithms, with a New One. Multiscale Modeling & Simulation, 4(2), 490-530.
  2. Dabov, K., Foi, A., Katkovnik, V. and Egiazarian, K., (2007). Image denoising by sparse 3-D transformdomain collaborative filtering. IEEE Transactions on Image Processing, 16(8), 2080-95.
  3. Dabov, K., Foi, A., Katkovnik, V. and Egiazarian, K., (2008). Image restoration by sparse 3D transformdomain collaborative filtering. Proceedings of SPIE, 213462(213462), 681207-12.
  4. Deledalle, C., Denis, L. and Tupin, F., (2009). Iterative weighted maximum likelihood denoising with probabilistic patch-based weights. IEEE Transactions on Image Processing, 18(12), 2661-72.
  5. Donoho, D. and Johnstone, J. M. (1994). Ideal spatial adaptation by wavelet shrinkage. Biometrika, 81(3), 425-455.
  6. Goossens, B. and Pizurica, A., (2009). Image denoising using mixtures of projected Gaussian scale mixtures. Image Processing, IEEE.
  7. Goossens, B., Luong, Q., Pizurica, A. and Philips, W., (2008). An improved non-local denoising algorithm. In 2008 Proc. Int. Workshop on Local and Non-Local Approximation in Image Processing. 1026-3.
  8. Parrilli, S., Poderico, M., Angelino, C. V. and Verdoliva, L., (2012). A Nonlocal S AR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage. IEEE Transactions on Geoscience and Remote Sensing (99), 1-11.
  9. Portilla, J., Strela, V., Wainwright, M. J. and Simoncelli, E. P., (2003). Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE transactions on image processing, 12(11), 1338-51.
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Paper Citation


in Harvard Style

Matrecano M., Poggi G. and Verdoliva L. (2012). IMPROVED BM3D FOR CORRELATED NOISE REMOVAL . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-03-7, pages 129-134. DOI: 10.5220/0003854101290134


in Bibtex Style

@conference{visapp12,
author={Marcella Matrecano and Giovanni Poggi and Luisa Verdoliva},
title={IMPROVED BM3D FOR CORRELATED NOISE REMOVAL},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={129-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003854101290134},
isbn={978-989-8565-03-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)
TI - IMPROVED BM3D FOR CORRELATED NOISE REMOVAL
SN - 978-989-8565-03-7
AU - Matrecano M.
AU - Poggi G.
AU - Verdoliva L.
PY - 2012
SP - 129
EP - 134
DO - 10.5220/0003854101290134