2 September 2009 Image denoising and quality assessment through the Renyi entropy
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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.
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Salvador Gabarda, Salvador Gabarda, Raphael Redondo, Raphael Redondo, Elena Gil, Elena Gil, Gabriel Cristóbal, Gabriel Cristóbal, } "Image denoising and quality assessment through the Renyi entropy", Proc. SPIE 7444, Mathematics for Signal and Information Processing, 744419 (2 September 2009); doi: 10.1117/12.826153; https://doi.org/10.1117/12.826153
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