Paper Info
Title
A novel predictor coefficient interpolation algorithm for enhancement of spatial resolution of images
Abstract
This paper presents a novel algorithm for enhancement of spatial resolution of images. The proposed algorithm estimates a Least square based predictor of lower order and interpolates the coefficients of higher order predictor. We have reduced the predictor order form p to (p-1) that results into a saving of computational power. The proposed algorithm is generic that can be used with most of the LS based interpolation algorithms reported in literature. We have shown that use of interpolated prediction coefficient causes insignificant loss in subjective as well as objective (PSNR) quality of the higher resolution (HR) image as compared with the PSNR obtained by the actual prediction coefficient and there is around 40% to 50% reduction in computational complexity.
Year
DOI
Venue
2010
10.1109/APCCAS.2010.5774999
Circuits and Systems
Keywords
Field
DocType
computational complexity,image enhancement,image resolution,least squares approximations,computational complexity,have,higher order predictor,higher resolution image,image enhancement,interpolated prediction coefficient,least square based predictor,predictor coefficient interpolation algorithm,spatial image resolution,Autoregression Modeling,Computational complexity,Image Interpolation,Least Square estimation
Least squares,Algorithm design,Interpolation,Algorithm,Prediction algorithms,Pixel,Image resolution,Mathematics,Image scaling,Computational complexity theory
Conference
ISBN
Citations 
PageRank 
978-1-4244-7454-7
0
0.34
References 
Authors
6
3
Name
Order
Citations
PageRank
Vinit Jakhetiya110212.89
Sunil Prasad Jaiswal2427.94
Anil Kumar Tiwari36517.51