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Constant-time Bilateral Filter using Spectral Decomposition

Sugimoto, K.; Breckon, T.P.; Kamata, S.

Constant-time Bilateral Filter using Spectral Decomposition Thumbnail


Authors

K. Sugimoto

S. Kamata



Abstract

This paper presents an efficient constant-time bilateral filter where constant-time means that computational complexity is independent of filter window size. Many state-of-the-art constant-time methods approximate the original bilateral filter by an appropriate combination of a series of convolutions. It is important for this framework to optimize the performance tradeoff between approximate accuracy and the number of convolutions. The proposed method achieves the optimal performance tradeoff in a least-squares manner by using spectral decomposition under the assumption that images consist of discrete intensities such as 8-bit images. This approach is essentially applicable to arbitrary range kernel. Experiments show that the proposed method outperforms state-of-the-art methods in terms of both computational complexity and approximate accuracy.

Citation

Sugimoto, K., Breckon, T., & Kamata, S. (2016). Constant-time Bilateral Filter using Spectral Decomposition. In Proc. Int. Conf. on Image Processing (3319-3323). https://doi.org/10.1109/ICIP.2016.7532974

Conference Name 2016 IEEE International Conference on Image Processing (ICIP).
Conference Location Phoenix, AZ, USA
Start Date Sep 25, 2016
End Date Sep 28, 2016
Acceptance Date Jul 12, 2016
Online Publication Date Aug 19, 2016
Publication Date 2016
Deposit Date Oct 3, 2016
Publicly Available Date Mar 29, 2024
Pages 3319-3323
Series ISSN 2381-8549
Book Title Proc. Int. Conf. on Image Processing
DOI https://doi.org/10.1109/ICIP.2016.7532974
Keywords image filtering, noise removal, smoothing, edge preserving filter, denoising
Public URL https://durham-repository.worktribe.com/output/1149656
Publisher URL https://breckon.org/toby/publications/papers/sugimoto16bilateral.pdf
Related Public URLs http://community.dur.ac.uk/toby.breckon/publications/papers/sugimoto16bilateral.pdf
Additional Information Date of Conference: 25-28 Sept. 2016

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Accepted Conference Proceeding (377 Kb)
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