Neural Networks Applied for impulse Noise Reduction from Digital Images

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Pablo Luiz Braga Soares
José Patrocínio da Silva

Abstract

This paper proposes the use of a new method for detecting and removing impulse noise from digital images based on the combination of two Artificial Neural Networks (ANN). The training algorithm of the ANNs is based on the technique of backpropagation. The first ANN is used to the detection of impulse noise, known as salt and pepper, and the second ANN is used to replace it by an estimated value. The proposed method is compared with other methods on literature in terms of visual judgment and also using a quantitative measure of PSNR - Peak Signal To Noise Ratio. The numerical and visual results obtained demonstrate the feasibility of the proposed method, which can be used as part of a tool for treatment of images.

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How to Cite
Soares, P. L. B., & Silva, J. P. da. (2012). Neural Networks Applied for impulse Noise Reduction from Digital Images. INFOCOMP Journal of Computer Science, 11(3-4), 7-14. Retrieved from http://infocomp.dcc.ufla.br/index.php/infocomp/article/view/358
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