Publication Type:

Journal Article

Source:

International Journal of Pure and Applied Mathematics, Volume 118 (2018)

URL:

https://acadpubl.eu/hub/2018-118-21/articles/21d/100.pdf

Abstract:

This paper is devoted to literature review of total variation based models to image denoising and restoration. In these
image denoising techniques the total variation of an image is minimized. Due to the increased need for good quality image in several
applications, an extensive research work has been done in the area image regularization with special focus on image denoising. Total
variation denoising is a mathematical approach developed to remove noise in an image and simultaneously preserve sharp edges in an
image. Unlike linear filters, total variation denoising is formulated as an optimization problem. This method of denoising produces
the denoised image by minimizing an energy functional or cost function. Therefore any numerical algorithm that can solve the
optimization problem can be used to implement total variation based image denoising. Total variation minimization concept is used
not only for denoising, but also for several image restoration methods such as in-painting, interpolation, deblurring and compressed
sensing.

Cite this Research Publication

V. Kamalaveni, Narayanankutty, K. A., S. Veni, and K. P. Soman, “Survey on Total Variation based Image Regularization Algorithms for Image Denoising”, International Journal of Pure and Applied Mathematics, vol. 118, 20 vol., 2018.