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Support vector machines based image interpolation correction scheme

  • School of Information Science and Engineering, Harbin Institute of Technology Weihai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationRough Sets and Knowledge Technology - First International Conference, RSKT 2006, Proceedings
PublisherSpringer Verlag
Pages679-684
Number of pages6
ISBN (Print)3540362975, 9783540362975
DOIs
StatePublished - 2006
Externally publishedYes
EventFirst International Conference on Rough Sets and Knowledge Technology, RSKT 2006 - Chongqing, China
Duration: 24 Jul 200626 Jul 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4062 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceFirst International Conference on Rough Sets and Knowledge Technology, RSKT 2006
Country/TerritoryChina
CityChongqing
Period24/07/0626/07/06

Keywords

  • Error correction
  • Image interpolation
  • Support vector machines
  • Support vector regression

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