Paper Info
Title
Image Interpolation Using Autoregressive Model and Gauss-Seidel Optimization.
Abstract
In this paper we propose a simple yet effective image interpolation algorithm based on autoregressive model. Unlike existing algorithms which rely on low resolution pixels to estimate interpolation coefficients, we optimize the interpolation coefficients and high resolution pixel values jointly from one optimization problem. Although the two sets of variables are coupled in the cost function, the problem can be effectively solved using Gauss-Seidel method. We prove the iterations are guaranteed to converge. Experiments show that on average we have over 3dB gain compared to bicubic interpolation and over 0.1dB gain compared to SAI.
Year
DOI
Venue
2011
10.1109/ICIG.2011.155
ICIG
Keywords
Field
DocType
effective image interpolation algorithm,gauss-seidel method,high resolution pixel,image interpolation,interpolation coefficient,optimization problem,gauss-seidel optimization,low resolution pixel,autoregressive model,cost function,image resolution,correlation,optimization,interpolation,convergence,gauss seidel,high resolution,iterative methods,low resolution
Nearest-neighbor interpolation,Spline interpolation,Computer science,Interpolation,Artificial intelligence,Linear interpolation,Mathematical optimization,Pattern recognition,Multivariate interpolation,Bicubic interpolation,Stairstep interpolation,Algorithm,Bilinear interpolation
Conference
Citations 
PageRank 
References 
8
0.59
4
Authors
5
Name
Order
Citations
PageRank
Ketan Tang110612.98
Oscar C. Au21592176.54
Lu Fang334355.27
Zhiding Yu442130.08
Yuanfang Guo59518.21