Noise Dismissal from Images Using Nonlinear Algorithms

Authors(2) :-P. Srinivasarao, Suresh Pabboju

Impulse noise reduction or removal is a very active research area of image processing. This paper presented a constrained optimization type of numerical algorithm for removing noise from images. The complete variation of the digital image is reduced subject to constraints involving the measurements of the noise. The parameters are imposed using Lagrange multipliers. The solution is secured using the gradient-projection method. This method uses a time dependent partial differential equation on a manifold determined by the boundary conditions. At time of zero the solution converges to a steady state condition results the de-noised image. It is very difficult to get image with normal methods this is over come by the numerical algorithm as it is simple and relatively fast. The results appear to be state-of-the-art for very noisy images. The method is asymptomatic, gives sharp edges in the image. The technique elucidate as a first step of moving each level set of the image normal to itself with velocity equal to the curvature of the level set divided by the magnitude of the direction of the image, and a second step which projects the image back onto the curtailment set.

Authors and Affiliations

P. Srinivasarao
Assistant Professor, IT Department CBIT, Hyderabad, Telangana, India
Suresh Pabboju
Professor, IT Department CBIT, Hyderabad, Telangana, India

Image processing, Lagrange multipliers, numerical algorithm

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Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 839-844
Manuscript Number : CSEIT1833264
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

P. Srinivasarao, Suresh Pabboju, "Noise Dismissal from Images Using Nonlinear Algorithms", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.839-844, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT1833264

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