International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 112

Research Paper | Information Technology | India | Volume 5 Issue 5, May 2016


Image Denoising Using Standard BP Algorithm

T. Uma Mageswari


Abstract: From the perspective of the Bayesian approach, the denoising problem is essentially a prior probability modeling and estimation task. In this paper, we propose an approach that exploits a hidden Bayesian network, constructed from wavelet coefficients, to model the prior probability of the original image. Then, we use the belief propagation (BP) algorithm, which estimates a coefficient based on all the coefficients of an image, as the maximum-a-posterior (MAP) estimator to derive the denoised wavelet coefficients. We show that if the network is a spanning tree, the standard BP algorithm can perform MAP estimation efficiently. Our experiment results demonstrate that, in terms of the peak-signal-to-noise-ratio and perceptual quality, the proposed approach outperforms state-of-the-art algorithms on several images, particularly in the textured regions, with various amounts of white Gaussian noise.


Keywords: IMAGE DENOISING


Edition: Volume 5 Issue 5, May 2016,


Pages: 1242 - 1252


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How to Cite this Article?

T. Uma Mageswari, "Image Denoising Using Standard BP Algorithm", International Journal of Science and Research (IJSR), Volume 5 Issue 5, May 2016, pp. 1242-1252, https://www.ijsr.net/get_abstract.php?paper_id=NOV163209

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