Support vector machines based image interpolation correction scheme

Authors:
Liyong Ma;Jiachen Ma;Yi Shen
Affiliations:
School of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai, P.R. China;School of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai, P.R. China;School of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai, P.R. China
Venue:
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Year:
2006

Citing 3
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Abstract

A novel error correction scheme for image interpolation algorithms based on support vector machines (SVMs) is proposed. SVMs are trained with the interpolation error distribution of down-sampled interpolated image to estimate interpolation error of the source image. Interpolation correction is employed to the interpolated result of source image with SVMs regression to obtain more accuracy result image. Error correction results of linear, cubic and warped distance adaptive interpolation algorithms demonstrate the effectiveness of the scheme