Compressive bilateral filtering

Research output: Contribution to journalArticle

40 Citations (Scopus)

Abstract

this paper presents an efficient constant-time bilateral filter that produces a near-optimal performance tradeoff between approximate accuracy and computational complexity without any complicated parameter adjustment, called a compressive bilateral filter (CBLF). The constant-time means that the computational complexity is independent of its filter window size. Although many existing constant-time bilateral filters have been proposed step-by-step to pursue a more efficient performance tradeoff, they have less focused on the optimal tradeoff for their own frameworks. It is important to discuss this question, because it can reveal whether or not a constant-time algorithm still has plenty room for improvements of performance tradeoff. This paper tackles the question from a viewpoint of compressibility and highlights the fact that state-of-the-art algorithms have not yet touched the optimal tradeoff. The CBLF achieves a near-optimal performance tradeoff by two key ideas: 1) an approximate Gaussian range kernel through Fourier analysis and 2) a period length optimization. Experiments demonstrate that the CBLF significantly outperforms state-of-the-art algorithms in terms of approximate accuracy, computational complexity, and usability.

Original languageEnglish
Article number7120121
Pages (from-to)3357-3369
Number of pages13
JournalIEEE Transactions on Image Processing
Volume24
Issue number11
DOIs
Publication statusPublished - 2015 Nov 1

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Computational complexity
Fourier analysis
Compressibility
Experiments

Keywords

  • Compressibility
  • Constant-time bilateral filtering
  • Edge-preserving smoothing

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Compressive bilateral filtering. / Sugimoto, Kenjiro; Kamata, Seiichiro.

In: IEEE Transactions on Image Processing, Vol. 24, No. 11, 7120121, 01.11.2015, p. 3357-3369.

Research output: Contribution to journalArticle

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