Article

A fast approximation of the bilateral filter using a signal processing approach

Authors:

Frédo DurandAuthors Info & Claims

ECCV'06: Proceedings of the 9th European conference on Computer Vision - Volume Part IV

Pages 568 - 580

https://doi.org/10.1007/11744085_44

Published: 07 May 2006 Publication History

Abstract

The bilateral filter is a nonlinear filter that smoothes a signal while preserving strong edges. It has demonstrated great effectiveness for a variety of problems in computer vision and computer graphics, and a fast version has been proposed. Unfortunately, little is known about the accuracy of such acceleration. In this paper, we propose a new signal-processing analysis of the bilateral filter, which complements the recent studies that analyzed it as a PDE or as a robust statistics estimator. Importantly, this signal-processing perspective allows us to develop a novel bilateral filtering acceleration using a downsampling in space and intensity. This affords a principled expression of the accuracy in terms of bandwidth and sampling. The key to our analysis is to express the filter in a higher-dimensional space where the signal intensity is added to the original domain dimensions. The bilateral filter can then be expressed as simple linear convolutions in this augmented space followed by two simple nonlinearities. This allows us to derive simple criteria for downsampling the key operations and to achieve important acceleration of the bilateral filter. We show that, for the same running time, our method is significantly more accurate than previous acceleration techniques.

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Index Terms

A fast approximation of the bilateral filter using a signal processing approach
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation

Index terms have been assigned to the content through auto-classification.

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Information

Published In

cover image Guide Proceedings

ECCV'06: Proceedings of the 9th European conference on Computer Vision - Volume Part IV

May 2006

613 pages

ISBN:3540338381

Editors:
Aleš Leonardis
University of Ljubljana, Slovenia
,
Horst Bischof
Institute for Computer Graphics and Vision, TU Graz, Inffeldgasse 16, Graz, Austria
,
Axel Pinz
Vision-based Measurement Group, Inst. of El. Measurement and Meas. Sign. Proc. Graz, University of Technology, Inffeldgasse 16, Graz, Austria

Sponsors

University of Ljubljana: University of Ljubljana
Graz University of Technology: Graz University of Technology
Advanced Computer Vision: Advanced Computer Vision

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 07 May 2006

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Cited By

Chen WHuang YWang MWu XZeng X(2024)KBStyle: Fast Style Transfer Using a 200 KB Network With Symmetric Knowledge DistillationIEEE Transactions on Image Processing10.1109/TIP.2023.333582833(82-94)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIP.2023.3335828
Song SZhong FWang TQin XTu C(2023)Guided Linear UpsamplingACM Transactions on Graphics10.1145/359245342:4(1-12)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592453
Oishi SFukushima N(2023)Tiling and PCA Strategy for Clustering-Based High-Dimensional Gaussian FilteringSN Computer Science10.1007/s42979-023-02319-65:1Online publication date: 29-Nov-2023
https://dl.acm.org/doi/10.1007/s42979-023-02319-6
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Liu WZhang PHuang XYang JShen CReid I(2020)Real-time Image Smoothing via Iterative Least SquaresACM Transactions on Graphics10.1145/338888739:3(1-24)Online publication date: 6-Jun-2020
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Xia XZhang MXue TSun ZFang HKulis BChen J(2020)Joint Bilateral Learning for Real-Time Universal Photorealistic Style TransferComputer Vision – ECCV 202010.1007/978-3-030-58598-3_20(327-342)Online publication date: 23-Aug-2020
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