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JOURNALS // Computer Optics // Archive

Computer Optics, 2015 Volume 39, Issue 4, Pages 564–571 (Mi co18)

This article is cited in 14 papers

IMAGE PROCESSING, PATTERN RECOGNITION

Image noise removal based on total variation

D. N. Thanh, S. D. Dvoenko

Tula State University

Abstract: Today, raster images are created by different modern devices, such as digital cameras, X-Ray scanners, and so on. Image noise deteriorates the image quality, thus adversely affecting the result of processing. Biomedical images are an example of digital images. The noise in such raster images is assumed to be a mixture of Gaussian noise and Poisson noise. In this paper, we propose a method to remove these noises based on the total variation of the image brightness function. The proposed model is a combination of two famous denoising models, namely, the ROF model and a modified ROF model.

Keywords: total variation, ROF model, Gaussian noise, Poisson noise, image processing, biomedical image, Euler-Lagrange equation.

Received: 14.07.2015
Revised: 28.07.2015

DOI: 10.18287/0134-2452-2015-39-4-564-571



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