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...

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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
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Madhu, T
Kishore, K Lal
description 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.
doi_str_mv 10.5120/21594-4689
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source Freely Accessible Science Journals - check A-Z of ejournals
subjects Algorithms
Density
Fuzzy
Impulses
Noise
Reconstruction
Regression
title Super Resolution Reconstruction in Mixed Noise Environment
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