Programs
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Publication Type : Conference Paper
Publisher : 7th International Conference on Computational Intelligence and Communication Networks (CICN 2015)
Source : 7th International Conference on Computational Intelligence and Communication Networks (CICN 2015), IEEE (2015)
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2015
Abstract : Image inpainting is the process of removing selected object and restoring dead pixel from an image based on the background information. Various method have been proposed to tackle the inpainting problem where they need related information from other images and use only neighboring data to recover the lost part of image. To overcome this, an efficient inpainting technique called Robust Non-Local Total variation Method (RNLTV) is used. For filling lost portion, the proposed method uses information from the image itself and also superiority of the local and non-local methods are put together here. The local method which is efficient for recovering image edges and the textured region is recovered using nonlocal method. A Bregman operator splitting algorithm is employed here to avoid the loss of signal in each iteration of the total variation. The efficiency of the Robust Non-Local Total Variation method was tested and compared with existing methods and found superior.
Cite this Research Publication :
D. Francis and Jyothisha J. Nair, “Robust Non-Local Total Variation Image Inpainting”, in 7th International Conference on Computational Intelligence and Communication Networks (CICN 2015), 2015