|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 9 - Issue 11 |
| Published: November 2010 |
| Authors: Muthukumar S, Dr.Krishnan .N, Pasupathi.P, Deepa . S |
10.5120/1431-1928
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Muthukumar S, Dr.Krishnan .N, Pasupathi.P, Deepa . S . Article:Analysis of Image Inpainting Techniques with Exemplar, Poisson, Successive Elimination and 8 Pixel Neighborhood Methods. International Journal of Computer Applications. 9, 11 (November 2010), 15-18. DOI=10.5120/1431-1928
@article{ 10.5120/1431-1928,
author = { Muthukumar S,Dr.Krishnan .N,Pasupathi.P,Deepa . S },
title = { Article:Analysis of Image Inpainting Techniques with Exemplar, Poisson, Successive Elimination and 8 Pixel Neighborhood Methods },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 9 },
number = { 11 },
pages = { 15-18 },
doi = { 10.5120/1431-1928 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A Muthukumar S
%A Dr.Krishnan .N
%A Pasupathi.P
%A Deepa . S
%T Article:Analysis of Image Inpainting Techniques with Exemplar, Poisson, Successive Elimination and 8 Pixel Neighborhood Methods%T
%J International Journal of Computer Applications
%V 9
%N 11
%P 15-18
%R 10.5120/1431-1928
%I Foundation of Computer Science (FCS), NY, USA
This paper discusses removing large objects from digital images and fills the hole that is left behind in a visually plausible way. We present a novel and efficient algorithm that fills the hole by exemplar-based synthesis. Here the simultaneous propagation of texture and structure information is achieved by a single, efficient algorithm. The texture image is repaired by the exemplar –based method; for the structure image, the Laplacian operator is employed to enhance the structure information, and the Laplacian image is inpainted by the exemplar-based algorithm, followed by a reconstruction based on the Poisson equation. To improve the computational efficiency of our algorithm we go for successive elimination algorithm (SEA). In 8 pixel neighborhood method, identifying central pixel value by investigating surrounded 8 neighborhood pixel properties like color variation, repetition, intensity and direction. Finally we compare speed and accuracy of a picture enhancement using 8 pixel neighborhood with exemplar based poisson & successive elimination method