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Proceedings Paper

Image denoising and quality assessment through the Renyi entropy
Author(s): Salvador Gabarda; Raphael Redondo; Elena Gil; Gabriel Cristóbal
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Paper Abstract

This paper presents a new image denoising method based on truncating the original noisy coefficients of a Pseudo- Wigner distribution (PWD) calculated through 1D directional windows. This method has been tested both for additive and multiplicative noisy images. The coefficients are selected according to their local directionality to take into account the image anisotropy. Next, the PWD is inverted and the set of different directional images are averaged. When the ground truth image reference is available, the peak signal-to-noise ratio (PSNR) metric is used to evaluate the resulting denoised images in comparison with other alternative methods. The described method is based on the use of the Renyi entropy extracted from a joint spatial frequency representation such as the Wigner distribution. A comparison with other competitive techniques is described and tested for real-world images. In particular, some experimental results are presented in the area of synthetic aperture radar (SAR) and retinal imaging, showing the effectiveness of the method in comparison with other alternative techniques through the use of two different non-reference image quality metrics.

Paper Details

Date Published: 2 September 2009
PDF: 11 pages
Proc. SPIE 7444, Mathematics for Signal and Information Processing, 744419 (2 September 2009); doi: 10.1117/12.826153
Show Author Affiliations
Salvador Gabarda, Instituto de Óptica, Consejo Superior de Investigaciones Científicas (Spain)
Raphael Redondo, Instituto de Óptica, Consejo Superior de Investigaciones Científicas (Spain)
Elena Gil, Instituto de Óptica, Consejo Superior de Investigaciones Científicas (Spain)
Gabriel Cristóbal, Instituto de Óptica, Consejo Superior de Investigaciones Científicas (Spain)


Published in SPIE Proceedings Vol. 7444:
Mathematics for Signal and Information Processing
Franklin T. Luk; Mark S. Schmalz; Gerhard X. Ritter; Junior Barrera; Jaakko T. Astola, Editor(s)

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