Processing of fused optical satellite images through parallel processing techniques in multi GPU

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Technology makes many of the tasks that were previously difficult to perform, nowadays can be solved, one of them is to be able to carry out studies on large tracts of land and at the same time be able to have a level of detail of them, through the study of the satellite images provided by the Earth...

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Detalles Bibliográficos
Autores: Auccahuasi, W., Castro, P., Flores, E., Sernaque, F., Garzon, A., Oré, E.
Formato: artículo
Fecha de Publicación:2020
Institución:Universidad Continental
Repositorio:CONTINENTAL-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.continental.edu.pe:20.500.12394/7562
Enlace del recurso:https://hdl.handle.net/20.500.12394/7562
https://doi.org/10.1016/j.procs.2020.03.307
Nivel de acceso:acceso abierto
Materia:Inteligencia artificial
Procesamiento de imágenes
Sistemas de imágenes tridimensionales
Satélites artificiales
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network_acronym_str UCON
network_name_str CONTINENTAL-Institucional
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dc.title.es_ES.fl_str_mv Processing of fused optical satellite images through parallel processing techniques in multi GPU
title Processing of fused optical satellite images through parallel processing techniques in multi GPU
spellingShingle Processing of fused optical satellite images through parallel processing techniques in multi GPU
Auccahuasi, W.
Inteligencia artificial
Procesamiento de imágenes
Sistemas de imágenes tridimensionales
Satélites artificiales
title_short Processing of fused optical satellite images through parallel processing techniques in multi GPU
title_full Processing of fused optical satellite images through parallel processing techniques in multi GPU
title_fullStr Processing of fused optical satellite images through parallel processing techniques in multi GPU
title_full_unstemmed Processing of fused optical satellite images through parallel processing techniques in multi GPU
title_sort Processing of fused optical satellite images through parallel processing techniques in multi GPU
author Auccahuasi, W.
author_facet Auccahuasi, W.
Castro, P.
Flores, E.
Sernaque, F.
Garzon, A.
Oré, E.
author_role author
author2 Castro, P.
Flores, E.
Sernaque, F.
Garzon, A.
Oré, E.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Auccahuasi, W.
Castro, P.
Flores, E.
Sernaque, F.
Garzon, A.
Oré, E.
dc.subject.es_ES.fl_str_mv Inteligencia artificial
Procesamiento de imágenes
Sistemas de imágenes tridimensionales
Satélites artificiales
topic Inteligencia artificial
Procesamiento de imágenes
Sistemas de imágenes tridimensionales
Satélites artificiales
description Technology makes many of the tasks that were previously difficult to perform, nowadays can be solved, one of them is to be able to carry out studies on large tracts of land and at the same time be able to have a level of detail of them, through the study of the satellite images provided by the Earth observation satellites, these images are composed of a series of spectral bands that will depend on the type of satellite mission that was conceived and the optical instrument that is found as a payload, these images are represented by multidimensional arrays and large size, so computational high computation equipment is required to process the images, added to this requires specialized software that allows the visual interpretation of satellite images. To be able to work with satellite images you have many configurations, normally you work with the configuration of separate bands that consists of working separately with each band of the image, these images have a particularity, the high resolution image is the one that is found in the Panchromatic band, where the maximum spatial resolution of the image is presented, which can range from metric to sub-metric, then the red, green, blue, and shortwave and wave infrared bands mean, these bands are in a lower range of spatial resolution for example if a satellite has a spatial resolution of 1 meter in the panchromatic and has 4 spectral bands (Red, Green, Blue, Near Infrared), these will have the resolution of 4 meters, so the level of detail is lost compared to panchromatic images. In order to improve this image performance we have the image configuration fused, where the resolution of all the bands including the color and infrared have the resolution of the panchromatic, this means that all are of resolution 1 meter, gaining resolution spatial and also this new configuration of the image has the color of the bands gaining spectral resolution, therefore these images have a greater weight in GB and its matrix increases in size, therefore it requires more processing time of the same, In the present article we present a technique that improves the processing time of the fused satellite images using parallel processing by using two graphic processors, with this the image processing task is distributed, as Matlab software was used as tool, because it allows us to manage multidimensional matrices and also allows us to der to have access to the graphic processor, we worked with 2 cards model GTX1050Ti of Nvidia.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-07-03T20:24:20Z
dc.date.available.none.fl_str_mv 2020-07-03T20:24:20Z
dc.date.created.none.fl_str_mv 2020
dc.date.issued.fl_str_mv 2020
dc.type.es_ES.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.citation.es_ES.fl_str_mv Auccahuasi, W., Castro, P., Flores, E., Sernaque, F., Garzon, A., Oré, E. (2020). Processing of fused optical satellite images through parallel processing techniques in multi GPU. Procedia Computer Science, 167, 2545-2553. https://doi.org/10.1016/j.procs.2020.03.307
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12394/7562
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.procs.2020.03.307
identifier_str_mv Auccahuasi, W., Castro, P., Flores, E., Sernaque, F., Garzon, A., Oré, E. (2020). Processing of fused optical satellite images through parallel processing techniques in multi GPU. Procedia Computer Science, 167, 2545-2553. https://doi.org/10.1016/j.procs.2020.03.307
url https://hdl.handle.net/20.500.12394/7562
https://doi.org/10.1016/j.procs.2020.03.307
dc.language.iso.es_ES.fl_str_mv eng
language eng
dc.relation.es_ES.fl_str_mv https://www.sciencedirect.com/science/article/pii/S1877050920307730?via%3Dihub
dc.rights.es_ES.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.accessRights.es_ES.fl_str_mv Acceso abierto
eu_rights_str_mv openAccess
rights_invalid_str_mv Acceso abierto
dc.format.es_ES.fl_str_mv application/pdf
dc.format.extent.es_ES.fl_str_mv p. 2545-2553
dc.publisher.es_ES.fl_str_mv Universidad Continental
dc.source.es_ES.fl_str_mv Universidad Continental
Repositorio Institucional - Continental
dc.source.none.fl_str_mv reponame:CONTINENTAL-Institucional
instname:Universidad Continental
instacron:CONTINENTAL
instname_str Universidad Continental
instacron_str CONTINENTAL
institution CONTINENTAL
reponame_str CONTINENTAL-Institucional
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spelling Auccahuasi, W.Castro, P.Flores, E.Sernaque, F.Garzon, A.Oré, E.2020-07-03T20:24:20Z2020-07-03T20:24:20Z20202020Auccahuasi, W., Castro, P., Flores, E., Sernaque, F., Garzon, A., Oré, E. (2020). Processing of fused optical satellite images through parallel processing techniques in multi GPU. Procedia Computer Science, 167, 2545-2553. https://doi.org/10.1016/j.procs.2020.03.307https://hdl.handle.net/20.500.12394/7562https://doi.org/10.1016/j.procs.2020.03.307Technology makes many of the tasks that were previously difficult to perform, nowadays can be solved, one of them is to be able to carry out studies on large tracts of land and at the same time be able to have a level of detail of them, through the study of the satellite images provided by the Earth observation satellites, these images are composed of a series of spectral bands that will depend on the type of satellite mission that was conceived and the optical instrument that is found as a payload, these images are represented by multidimensional arrays and large size, so computational high computation equipment is required to process the images, added to this requires specialized software that allows the visual interpretation of satellite images. To be able to work with satellite images you have many configurations, normally you work with the configuration of separate bands that consists of working separately with each band of the image, these images have a particularity, the high resolution image is the one that is found in the Panchromatic band, where the maximum spatial resolution of the image is presented, which can range from metric to sub-metric, then the red, green, blue, and shortwave and wave infrared bands mean, these bands are in a lower range of spatial resolution for example if a satellite has a spatial resolution of 1 meter in the panchromatic and has 4 spectral bands (Red, Green, Blue, Near Infrared), these will have the resolution of 4 meters, so the level of detail is lost compared to panchromatic images. In order to improve this image performance we have the image configuration fused, where the resolution of all the bands including the color and infrared have the resolution of the panchromatic, this means that all are of resolution 1 meter, gaining resolution spatial and also this new configuration of the image has the color of the bands gaining spectral resolution, therefore these images have a greater weight in GB and its matrix increases in size, therefore it requires more processing time of the same, In the present article we present a technique that improves the processing time of the fused satellite images using parallel processing by using two graphic processors, with this the image processing task is distributed, as Matlab software was used as tool, because it allows us to manage multidimensional matrices and also allows us to der to have access to the graphic processor, we worked with 2 cards model GTX1050Ti of Nvidia.application/pdfp. 2545-2553engUniversidad Continentalhttps://www.sciencedirect.com/science/article/pii/S1877050920307730?via%3Dihubinfo:eu-repo/semantics/openAccessAcceso abiertoUniversidad ContinentalRepositorio Institucional - Continentalreponame:CONTINENTAL-Institucionalinstname:Universidad Continentalinstacron:CONTINENTALInteligencia artificialProcesamiento de imágenesSistemas de imágenes tridimensionalesSatélites artificialesProcessing of fused optical satellite images through parallel processing techniques in multi GPUinfo:eu-repo/semantics/articleLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.continental.edu.pe/bitstream/20.500.12394/7562/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5120.500.12394/7562oai:repositorio.continental.edu.pe:20.500.12394/75622020-07-08 16:59:14.043Repositorio Continentaldspaceconti@continental.edu.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