GPU-friendly Approximate Bilateral Filter for 3D Volume Data

Koichi Yano, Kenjiro Sugimoto, Sei Ichiro Kamata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an approximate Bilateral Filter(BF) with a GPU-friendly architecture for 3D volume data. The bilateral filter (BF) for 3D volume data such as medical images highly costs due to an enormous number of voxels to be processed. Existing acceleration methods called constant-time, or O(1), BF are inappropriate for GPU processing because they consist of a combination of O(1) spatial filters not to fit to parallel processing. The proposed method realizes a fast approximation 3D-BF by focusing two points: (1) the BF is decomposed into multiple Gaussian Filters and (2) GPU processing is suitable for convolution. As a consequence, proposed method achieved fast and high approximate accuracy in various window size.

Original languageEnglish
Title of host publication2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2054-2058
Number of pages5
ISBN (Electronic)9789881476852
DOIs
Publication statusPublished - 2019 Mar 4
Event10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Honolulu, United States
Duration: 2018 Nov 122018 Nov 15

Publication series

Name2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings

Conference

Conference10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
Country/TerritoryUnited States
CityHonolulu
Period18/11/1218/11/15

ASJC Scopus subject areas

  • Information Systems

Fingerprint

Dive into the research topics of 'GPU-friendly Approximate Bilateral Filter for 3D Volume Data'. Together they form a unique fingerprint.

Cite this