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Development of Optimal Denoising Technique using TV Regularization and Masking Filter

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Vivek Kumar Sharma, Shreeja Nair
10.5120/ijca2016911092

Vivek Kumar Sharma and Shreeja Nair. Development of Optimal Denoising Technique using TV Regularization and Masking Filter. International Journal of Computer Applications 151(5):1-5, October 2016. BibTeX

@article{10.5120/ijca2016911092,
	author = {Vivek Kumar Sharma and Shreeja Nair},
	title = {Development of Optimal Denoising Technique using TV Regularization and Masking Filter},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {151},
	number = {5},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume151/number5/26226-2016911092},
	doi = {10.5120/ijca2016911092},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Image denoising is the fascinating research area among researchers due to applications of the images in everywhere, social networking sites, High Definition videos and stills. The need of it is to enhance the facility to imaging devices and the processing devices for denoising and enhancement of images. In this paper, Total Variation (TV) regularization is used to allow for accurate registration near such boundaries. We propose a novel formulation of TV-regularization for parametric displacement fields and Masking Filter to enhance or denoising of images. The proposed methodology's performance are usually compared in terms of peak-signal-to-noise ratio (PSNR). These are simply mathematically defined image metrics that take care of noise power level in the whole image.

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Keywords

PSNR, Image Denoising, TV, Masking Filter.