Sanchez, G.; Vidal Gimeno, VE.; Bataller Mascarell, J. (2012). Peer group and fuzzy metric to remove noise in images using heterogeneous computing. En Euro-Par 2011: Parallel Processing Workshops. Springer Verlag (Germany). 7155:502-510. https://doi.org/10.1007/978-3-642-29737-3
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/36969
Título:
|
Peer group and fuzzy metric to remove noise in images using heterogeneous computing
|
Autor:
|
Sanchez, Guadalupe
Vidal Gimeno, Vicente Emilio
Bataller Mascarell, Jordi
|
Entidad UPV:
|
Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
|
Fecha difusión:
|
|
Resumen:
|
In this paper, we report a study on the parallelization of an algorithm
for removing impulsive noise in images. The algorithm is based on the concept
of peer group and fuzzy metric. We have developed implementations ...[+]
In this paper, we report a study on the parallelization of an algorithm
for removing impulsive noise in images. The algorithm is based on the concept
of peer group and fuzzy metric. We have developed implementations using
Open Multi-Processing (OpenMP) and Compute Unified Device Architecture
(CUDA) for Graphics Processing Unit (GPU). Many sequential algorithms have
been proposed to remove noise, but their computational cost is excessive for
real-time processing of large images. We developed implementations for a multi-
core CPU, for a multi-GPU (several GPUs) and for a combination of both.
These implementations were compared also with different sizes of the image in
order to find out the settings with the best performance. A study is made using
the shared memory and texture memory to minimize access time to data in GPU
global memory. The result shows that when the image is distributed in multicore
and multi-GPU a greater number of Mpixels/second are processed.
[-]
|
Palabras clave:
|
Remove impulsive noise
,
Peer group
,
Fuzzy metric
,
Parallel algorithm
,
CUDA
,
OpenMP
,
Multi-core
,
Multi-GPU
|
Derechos de uso:
|
Cerrado |
ISBN:
|
978-3-642-29736-6
|
Fuente:
|
Euro-Par 2011: Parallel Processing Workshops. (issn:
0302-9743
)
|
DOI:
|
10.1007/978-3-642-29737-3
|
Editorial:
|
Springer Verlag (Germany)
|
Versión del editor:
|
http://link.springer.com/chapter/10.1007/978-3-642-29737-3_55
|
Título del congreso:
|
CCPI, CGWS, HeteroPar, HiBB, HPCVirt, HPPC, HPSS, MDGS, ProPer, Resilience, UCHPC, VHPC, 2011
|
Lugar del congreso:
|
Bordeaux, France
|
Fecha congreso:
|
August 29 - September 2, 2011
|
Serie:
|
Lecture Notes in Computer Science;vol. 7155
|
Código del Proyecto:
|
info:eu-repo/grantAgreement/MICINN//TIN2008-06570-C04-04/ES/CONSTRUCCION Y OPTIMIZACION AUTOMATICAS DE BIBLIOTECAS PARALELAS DE COMPUTACION CIENTIFICA - UA/
|
Agradecimientos:
|
This work was funded by the Spanish Ministry of Science and
Innovation (Project TIN2008-06570-C04-04) and M. Guadalupe would also like to
acknowledge DGEST ITCG for the scholarship awarded through the PROMEP
program (Mexico)[+]
This work was funded by the Spanish Ministry of Science and
Innovation (Project TIN2008-06570-C04-04) and M. Guadalupe would also like to
acknowledge DGEST ITCG for the scholarship awarded through the PROMEP
program (Mexico)
[-]
|
Tipo:
|
Capítulo de libro
|