Fast image filtering by DCT-based kernel decomposition and sequential sum update

Kenjiro Sugimoto*, Sei Ichiro Kamata

*この研究の対応する著者

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

This paper presents an approximate Gaussian filter which can run in one-pass with high accuracy based on spectrum sparsity. This method is a modification of the cosine integral image (CII), which decomposes a filter kernel into few cosine terms and convolves each cosine term with an input image in constant time per pixel by using integral images and look-up tables. However, they require much workspace and high access cost. The proposed method solves the problem with no decline in quality by sequentially updating sums instead of integral images and by improving look-up tables, which accomplishes a one-pass approximation with much less workspace. A specialization for tiny kernels are also discussed for faster calculation. Experiments on image filtering show that the proposed method can run nearly two times faster than CII and also than convolution even with small kernel.

本文言語English
ホスト出版物のタイトル2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
ページ125-128
ページ数4
DOI
出版ステータスPublished - 2012 12月 1
イベント2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
継続期間: 2012 9月 302012 10月 3

出版物シリーズ

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

Conference

Conference2012 19th IEEE International Conference on Image Processing, ICIP 2012
国/地域United States
CityLake Buena Vista, FL
Period12/9/3012/10/3

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 情報システム

フィンガープリント

「Fast image filtering by DCT-based kernel decomposition and sequential sum update」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル