A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery
A novel parallel tool for large-scale image enhancement/reconstruction and postprocessing of radar/SAR sensor systems is addressed. The proposed parallel tool performs the following intelligent processing steps: image formation, for the application of different system-level effects of image degradat...
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Series: | Mathematical Problems in Engineering |
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doaj-c000a556a94d400c964bfbfede25c3372020-11-24T23:20:36ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/405372405372A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed ImageryA. Castillo Atoche0R. Carrasco Alvarez1J. Ortegón Aguilar2J. Vázquez Castillo3Universidad Autónoma de Yucatán, Avenida Industrias No Contaminantes S/N, Apartado Postal 150, 97310 Mérida, YUC, MexicoUniversidad de Guadalajara, Boulevard Marcelino García Barragán1421, 44430 Guadalajara, JAL, MexicoUniversidad de Quintana Roo, Boulevard Bahía S/N Esquina Ignacio Comonfort, 77019 Chetumal, QROO, MexicoUniversidad de Quintana Roo, Boulevard Bahía S/N Esquina Ignacio Comonfort, 77019 Chetumal, QROO, MexicoA novel parallel tool for large-scale image enhancement/reconstruction and postprocessing of radar/SAR sensor systems is addressed. The proposed parallel tool performs the following intelligent processing steps: image formation, for the application of different system-level effects of image degradation with a particular remote sensing (RS) system and simulation of random noising effects, enhancement/reconstruction by employing nonparametric robust high-resolution techniques, and image postprocessing using the fuzzy anisotropic diffusion technique which incorporates a better edge-preserving noise removal effect and faster diffusion process. This innovative tool allows the processing of high-resolution images provided with different radar/SAR sensor systems as required by RS endusers for environmental monitoring, risk prevention, and resource management. To verify the performance implementation of the proposed parallel framework, the processing steps are developed and specifically tested on graphic processing units (GPU), achieving considerable speedups compared to the serial version of the same techniques implemented in C language.http://dx.doi.org/10.1155/2013/405372 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. Castillo Atoche R. Carrasco Alvarez J. Ortegón Aguilar J. Vázquez Castillo |
spellingShingle |
A. Castillo Atoche R. Carrasco Alvarez J. Ortegón Aguilar J. Vázquez Castillo A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery Mathematical Problems in Engineering |
author_facet |
A. Castillo Atoche R. Carrasco Alvarez J. Ortegón Aguilar J. Vázquez Castillo |
author_sort |
A. Castillo Atoche |
title |
A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery |
title_short |
A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery |
title_full |
A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery |
title_fullStr |
A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery |
title_full_unstemmed |
A New Tool for Intelligent Parallel Processing of Radar/SAR Remotely Sensed Imagery |
title_sort |
new tool for intelligent parallel processing of radar/sar remotely sensed imagery |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2013-01-01 |
description |
A novel parallel tool for large-scale image enhancement/reconstruction and postprocessing of radar/SAR sensor systems is addressed. The proposed parallel tool performs the following intelligent processing steps: image formation, for the application of different system-level effects of image degradation with a particular remote sensing (RS) system and simulation of random noising effects, enhancement/reconstruction by employing nonparametric robust high-resolution techniques, and image postprocessing using the fuzzy anisotropic diffusion technique which incorporates a better edge-preserving noise removal effect and faster diffusion process. This innovative tool allows the processing of high-resolution images provided with different radar/SAR sensor systems as required by RS endusers for environmental monitoring, risk prevention, and resource management. To verify the performance implementation of the proposed parallel framework, the processing steps are developed and specifically tested on graphic processing units (GPU), achieving considerable speedups compared to the serial version of the same techniques implemented in C language. |
url |
http://dx.doi.org/10.1155/2013/405372 |
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