Fixed-coefficient iterative bilateral filters for graph-based image processing

Chang Jian; Kohei Inoue; Kenji Hara; Kiichi Urahama

doi:10.1007/978-3-540-92957-4_41

Fixed-coefficient iterative bilateral filters for graph-based image processing

Chang Jian, Kohei Inoue, Kenji Hara, Kiichi Urahama

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

Abstract

We present a graph-based image processing algorithm using fast iterative bilateral filters. The computation of bilateral filters is accelerated with fixation of the coefficients during iterations and their approximate decomposition further speeds up the computation. We show that this fixed-coefficient iterative bilateral filter is an alternative solver for optimization problems in graph-based data analyses and apply its fast algorithm to graph-based image processing tasks. Performance of the present algorithm is demonstrated with experiments of contrast enhancement and smoothing of images using cross bilateral filters, in addition to semi-supervised image segmentation and colorization of monochromatic images.

Original language	English
Pages (from-to)	473-484
Number of pages	12
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5414 LNCS
DOIs	https://doi.org/10.1007/978-3-540-92957-4_41
Publication status	Published - 2009
Event	3rd Pacific Rim Symposium on Image and Video Technology, PSIVT 2009 - Tokyo, Japan Duration: Jan 13 2009 → Jan 16 2009

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

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10.1007/978-3-540-92957-4_41

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Fixed-coefficient iterative bilateral filters for graph-based image processing. / Jian, Chang; Inoue, Kohei ; Hara, Kenji et al.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5414 LNCS, 2009, p. 473-484.

Research output: Contribution to journal › Conference article › peer-review

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AU - Inoue, Kohei

AU - Hara, Kenji

AU - Urahama, Kiichi

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Y1 - 2009

N2 - We present a graph-based image processing algorithm using fast iterative bilateral filters. The computation of bilateral filters is accelerated with fixation of the coefficients during iterations and their approximate decomposition further speeds up the computation. We show that this fixed-coefficient iterative bilateral filter is an alternative solver for optimization problems in graph-based data analyses and apply its fast algorithm to graph-based image processing tasks. Performance of the present algorithm is demonstrated with experiments of contrast enhancement and smoothing of images using cross bilateral filters, in addition to semi-supervised image segmentation and colorization of monochromatic images.

AB - We present a graph-based image processing algorithm using fast iterative bilateral filters. The computation of bilateral filters is accelerated with fixation of the coefficients during iterations and their approximate decomposition further speeds up the computation. We show that this fixed-coefficient iterative bilateral filter is an alternative solver for optimization problems in graph-based data analyses and apply its fast algorithm to graph-based image processing tasks. Performance of the present algorithm is demonstrated with experiments of contrast enhancement and smoothing of images using cross bilateral filters, in addition to semi-supervised image segmentation and colorization of monochromatic images.

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JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Y2 - 13 January 2009 through 16 January 2009

ER -

Fixed-coefficient iterative bilateral filters for graph-based image processing

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