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

Chang Jian, Kohei Inoue, Hara Kenji, Kiichi Urahama

Research output: Contribution to journalConference article

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 languageEnglish
Pages (from-to)473-484
Number of pages12
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5414 LNCS
DOIs
Publication statusPublished - Feb 19 2009
Event3rd Pacific Rim Symposium on Image and Video Technology, PSIVT 2009 - Tokyo, Japan
Duration: Jan 13 2009Jan 16 2009

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Bilateral Filter
Image Processing
Image processing
Coefficient
Graph in graph theory
Fast Algorithm
Image segmentation
Contrast Enhancement
Fixation
Image Segmentation
Decomposition
Smoothing
Speedup
Optimization Problem
Iteration
Decompose
Alternatives
Experiments
Experiment

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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AU - Jian, Chang

AU - Inoue, Kohei

AU - Kenji, Hara

AU - Urahama, Kiichi

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Y1 - 2009/2/19

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

JF - Lecture Notes in Computer Science

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