Constant-time bilateral filter using spectral decomposition

Kenjiro Sugimoto, Toby Breckon, Sei Ichiro Kamata

研究成果: Conference contribution

10 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
出版社IEEE Computer Society
ページ3319-3323
ページ数5
ISBN(電子版)9781467399616
DOI
出版ステータスPublished - 2016 8 3
イベント23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
継続期間: 2016 9 252016 9 28

出版物シリーズ

名前Proceedings - International Conference on Image Processing, ICIP
2016-August
ISSN(印刷版)1522-4880

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
国/地域United States
CityPhoenix
Period16/9/2516/9/28

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • 信号処理

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