Super Resolution Reconstruction in Mixed Noise Environment

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 ba...

Full description

Saved in:
Bibliographic Details
Published in:International journal of computer applications 2015-01, Vol.121 (12), p.33-41
Main Authors: Devi, A Geetha, Madhu, T, Kishore, K Lal
Format: Article
Language:English
Subjects:
Algorithms
Density
Fuzzy
Impulses
Noise
Reconstruction
Regression
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0975-8887
0975-8887
DOI:10.5120/21594-4689