<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper presents a context-based filter to denoise grayscale images affected by random valued impulse noise. A support vector machine classifier is used for noise detection and two Markov filter variants are evaluated for their denoising capacity. The classifier needs to be trained on a set of training images. The experiments performed on another set of test images have shown that the support vector machine with the radial basis function kernel combined with the Markov+ filter is the best configuration, providing the highest noise detection accuracy. Our filter was compared with existing denoising methods, it being better on some images and comparable with them on others.</p>
</abstract>

This paper presents a context-based filter to denoise grayscale images affected by random valued impulse noise. A support vector machine classifier is used for noise detection and two Markov filter variants are evaluated for their denoising capacity. The classifier needs to be trained on a set of training images. The experiments performed on another set of test images have shown that the support vector machine with the radial basis function kernel combined with the Markov+ filter is the best configuration, providing the highest noise detection accuracy. Our filter was compared with existing denoising methods, it being better on some images and comparable with them on others.

Filtering Random Valued Impulse Noise from Grayscale Images through Support Vector Machine and Markov Chain

Computer Science and Electrical and Electronics Engineering Department, Faculty of Engineering

International Journal of Advanced Statistics and IT&C for Economics and Life Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This paper presents a context-based filter to denoise grayscale images affected by random valued impulse noise. A support vector machine classifier is used for...

Filtering Random Valued Impulse Noise from Grayscale Images through Support Vector Machine and Markov Chain

Online veröffentlicht: 30. Dez. 2021

Seitenbereich: 70 - 84

DOI: https://doi.org/10.2478/ijasitels-2021-0004

Schlüsselwörter
random valued impulse noise, support vector machine, Markov filter, denoising

© 2021 Arpad Gellert et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Filtering Random Valued Impulse Noise from Grayscale Images through Support Vector Machine and Markov Chain

Online veröffentlicht: 30. Dez. 2021

Seitenbereich: 70 - 84

DOI: https://doi.org/10.2478/ijasitels-2021-0004

Schlüsselwörterrandom valued impulse noise, support vector machine, Markov filter, denoising

© 2021 Arpad Gellert et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
random valued impulse noise, support vector machine, Markov filter, denoising