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Edge-aware filtering with local polynomial approximation and rectangle based weighting
Department of Computer Science, University of Hong Kong, Hong Kong.
CSIRO Digital Productivity, Sydney, NSW, Australia.
Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-4255-5130
2016 (English)In: IEEE Transactions on Cybernetics, ISSN 2168-2267, E-ISSN 2168-2275, Vol. 46, no 12, 2693-2705 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel method for performing guided image filtering using local polynomial approximation (LPA) with range guidance. In our method, the LPA is introduced into a multipoint framework for reliable model regression and better preservation on image spatial variation which usually contains the essential information in the input image. In addition, we develop a weighting scheme which has the spatial flexibility during the filtering process. All components in our method are efficiently implemented and a constant computation complexity is achieved. Compared with conventional filtering methods, our method provides clearer boundaries and performs especially better in recovering spatial variation from noisy images. We conduct a number of experiments for different applications: depth image upsampling, joint image denoising, details enhancement, and image abstraction. Both quantitative and qualitative comparisons demonstrate that our method outperforms state-of-the-art methods.

Place, publisher, year, edition, pages
IEEE Press, 2016. Vol. 46, no 12, 2693-2705 p.
Keyword [en]
Computer vision, depth enhancement, edgeaware filtering, local polynomial regression, rectangular
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-124599DOI: 10.1109/TCYB.2015.2485203ISI: 000388923100002PubMedID: 26513818Scopus ID: 2-s2.0-85027713629OAI: oai:DiVA.org:liu-124599DiVA: diva2:901030
Available from: 2016-02-05 Created: 2016-02-05 Last updated: 2018-01-10Bibliographically approved

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Pham, Tuan

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf