Implementation of non local means filter in GPUs

Adrián Márques, Alvaro Pardo

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

14 Citas (Scopus)

Resumen

In this paper, we review some alternatives to reduce the computational complexity of the Non-Local Means image filter and present a CUDA-based implementation of it for GPUs, comparing its performance on different GPUs and with respect to reference CPU implementations. Starting from a naive CUDA implementation, we describe different aspects of CUDA and the algorithm itself that can be leveraged to decrease the execution time. Our GPU implementation achieved speedups of up to 35.8x with respect to our reduced-complexity reference implementation on the CPU, and more than 700x over a plain CPU implementation.

Idioma originalInglés
Título de la publicación alojadaProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 18th Iberoamerican Congress, CIARP 2013, Proceedings
Páginas407-414
Número de páginas8
EdiciónPART 1
DOI
EstadoPublicada - 2013
Evento18th Iberoamerican Congress on Pattern Recognition, CIARP 2013 - Havana
Duración: 20 nov. 201323 nov. 2013

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 1
Volumen8258 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia18th Iberoamerican Congress on Pattern Recognition, CIARP 2013
País/TerritorioCuba
CiudadHavana
Período20/11/1323/11/13

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