Debluring low-resolution images

Jinshan Pan, Zhe Hu, Zhixun Su, Ming Hsuan Yang

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

2 Citations (Scopus)

Abstract

The recent years have witnessed significant advances in image deblurring. In general, the success of deblurring methods depends heavily on extraction of salient structures from a blurry image for kernel estimation. Most deblurring methods often operate on high-resolution images where contours or edges can be extracted for kernel estimation. However, recovering reliable structures from low-resolution images becomes extremely challenging. In this paper, we propose a spatially variant deblurring algorithm for low-resolution images based on the exemplars. To exploit the exemplar information, we develop a super-resolution guided method to help the restoration of reliable image structures which can be used for kernel estimation. Experimental evaluations against the state-of-the-art methods show that the proposed algorithm performs favorably in deblurring low-resolution images. Furthermore, we show that the SR results obtained as byproducts in our method are comparable compared to other blind SR methods.

Original languageEnglish
Title of host publicationComputer Vision - ACCV 2016 Workshops - ACCV 2016 International Workshops, Revised Selected Papers
EditorsJiwen Lu, Kai-Kuang Ma, Chu-Song Chen
PublisherSpringer Verlag
Pages111-127
Number of pages17
ISBN (Print)9783319544069
DOIs
Publication statusPublished - 2017 Jan 1
Event13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan, Province of China
Duration: 2016 Nov 202016 Nov 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10116 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th Asian Conference on Computer Vision, ACCV 2016
CountryTaiwan, Province of China
City Taipei
Period16/11/2016/11/24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Pan, J., Hu, Z., Su, Z., & Yang, M. H. (2017). Debluring low-resolution images. In J. Lu, K-K. Ma, & C-S. Chen (Eds.), Computer Vision - ACCV 2016 Workshops - ACCV 2016 International Workshops, Revised Selected Papers (pp. 111-127). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10116 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-54407-6_8