An efficient super resolution algorithm using simple linear regression

Shen-Chuan Tai, Tse Ming Kuo, Kuo Hao Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

With the improvement in technology of thin-filmtransistor liquid-crystal display (TFT-LCD), the resolution requirement of display becomes higher and higher. Super-resolution algorithms are used to enlarge original low-resolution (LR) images to meet the visual quality of the high-resolution (HR) display. In this research, an efficient super resolution algorithm is proposed. The proposed algorithm consists of two steps. First, the Lanczos interpolation is used for LR images to get the preliminary HR images. For solving the over-smoothing problems generally caused by interpolation, it needs to add texture information to refine the preliminary HR images. Subsequently, a refinement process based on simple linear regression and the self-similarity between a pair of LR and HR images is performed to provide proper information of textures. In the experimental results, the proposed algorithm not only performs well in the objective measurement such as PSNR, but also in visual qualities.

Original languageEnglish
Title of host publicationProceedings - 2013 2nd International Conference on Robot, Vision and Signal Processing, RVSP 2013
PublisherIEEE Computer Society
Pages287-290
Number of pages4
ISBN (Print)9781479931842
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 2nd International Conference on Robot, Vision and Signal Processing, RVSP 2013 - Kitakyushu, Japan
Duration: 2013 Dec 102013 Dec 12

Publication series

NameProceedings - 2013 2nd International Conference on Robot, Vision and Signal Processing, RVSP 2013

Other

Other2013 2nd International Conference on Robot, Vision and Signal Processing, RVSP 2013
CountryJapan
CityKitakyushu
Period13-12-1013-12-12

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Signal Processing

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