Local covariance filtering for color images

Keiichiro Shirai, Masahiro Okuda, Takao Jinno, Masayuki Okamoto, Masaaki Ikehara

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

2 Citations (Scopus)


In this paper, we introduce a novel edge-aware filter that manipulates the local covariances of a color image. A covariance matrix obtained at each pixel is decomposed by the singular value decomposition (SVD), then diagonal eigenvalues are filtered by characteristic control functions. Our filter form generalizes a wide class of edge-aware filters. Once the SVDs are calculated, users can control the filter characteristic graphically by modifying the curve of the characteristic control functions, just like tone curve manipulation while seeing a result in real-time. We also introduce an efficient iterative calculation of the pixel-wise SVD which is able to significantly reduce its execution time.

Original languageEnglish
Title of host publicationComputer Vision, ACCV 2012 - 11th Asian Conference on Computer Vision, Revised Selected Papers
Number of pages12
EditionPART 4
Publication statusPublished - 2013
Event11th Asian Conference on Computer Vision, ACCV 2012 - Daejeon, Korea, Republic of
Duration: 2012 Nov 52012 Nov 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume7727 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other11th Asian Conference on Computer Vision, ACCV 2012
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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