|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 121 - Issue 12 |
| Published: July 2015 |
| Authors: A.Geetha Devi, T.Madhu, K.Lal Kishore |
10.5120/21594-4689
|
A.Geetha Devi, T.Madhu, K.Lal Kishore . Super Resolution Reconstruction in Mixed Noise Environment. International Journal of Computer Applications. 121, 12 (July 2015), 33-41. DOI=10.5120/21594-4689
@article{ 10.5120/21594-4689,
author = { A.Geetha Devi,T.Madhu,K.Lal Kishore },
title = { Super Resolution Reconstruction in Mixed Noise Environment },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 121 },
number = { 12 },
pages = { 33-41 },
doi = { 10.5120/21594-4689 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A A.Geetha Devi
%A T.Madhu
%A K.Lal Kishore
%T Super Resolution Reconstruction in Mixed Noise Environment%T
%J International Journal of Computer Applications
%V 121
%N 12
%P 33-41
%R 10.5120/21594-4689
%I Foundation of Computer Science (FCS), NY, USA
A hybrid Super Resolution (SR) algorithm is proposed to deal with the Low Resolution (LR) images degraded by Mixed (Gaussian + Impulse) noise. The algorithm adaptively estimates and removes the impulse noise from the input LR images based on edge, geometrical & size characteristics. The fuzzy based impulse noise removal algorithm is along with adaptive sharpening filter based SR using steering kernel regression are used to obtain a HR image. The experimental results confirm the efficacy of the algorithm for different types of images at various noise densities.