Example selective and order independent learning-based image super-resolution

Min Chen, Guoping Qiu, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)

Abstract

In this paper, we present a novel example selective and order independent method for learning-based image super-resolution. We first present a method that selectively utilizes training samples according to the content of the input image. Experimental results show that by selecting the training samples appropriately, it is possible to dramatically reduce the computational costs without degrading image quality. We then present a new order independent technique that is shown to perform better than traditional order dependent techniques in learning image super-resolution and can also be applied to image editing such as region filling and object removal from images
Original languageEnglish
Title of host publicationProceedings of 2005 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2005
Pages77-80
Number of pages4
Volume2005
Publication statusPublished - 1 Dec 2005
Event2005 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2005 - Hong Kong, Hong Kong
Duration: 13 Dec 200516 Dec 2005

Conference

Conference2005 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2005
Country/TerritoryHong Kong
CityHong Kong
Period13/12/0516/12/05

ASJC Scopus subject areas

  • Engineering(all)

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