3D Non-Local Means denoising via multi-GPU

Giuseppe Palma, Marco Comerci, Bruno Alfano, Salvatore Cuomo, Pasquale De Michele, Francesco Piccialli, Pasquale Borrelli

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

Abstract

Non-Local Means (NLM) algorithm is widely considered as a state-of-the-art denoising filter in many research fields. High computational complexity led to implementations on Graphic Processor Unit (GPU) architectures, which achieve reasonable running times by filtering, slice-by-slice, 3D datasets with a 2D NLM approach. Here we present a fully 3D NLM implementation on a multi-GPU architecture and suggest its high scalability. The performance results we discuss encourage the coding of further filter improvements and the investigation of a large spectrum of applicative scenarios.

Original languageEnglish
Title of host publication2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013
Pages495-498
Number of pages4
Publication statusPublished - 2013
Event2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013 - Krakow, Poland
Duration: Sep 8 2013Sep 11 2013

Other

Other2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013
CountryPoland
CityKrakow
Period9/8/139/11/13

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems

Fingerprint Dive into the research topics of '3D Non-Local Means denoising via multi-GPU'. Together they form a unique fingerprint.

Cite this