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Remote Sens. 2014, 6(7), 6039-6063; doi:10.3390/rs6076039

A Parallel Computing Paradigm for Pan-Sharpening Algorithms of Remotely Sensed Images on a Multi-Core Computer

1
School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
2
Chinese Academy of Surveying and Mapping (CASM), Beijing 100830, China
*
Author to whom correspondence should be addressed.
Received: 4 April 2014 / Revised: 17 June 2014 / Accepted: 19 June 2014 / Published: 27 June 2014
(This article belongs to the Special Issue Remote Sensing Dedicated to Geographical Conditions Monitoring)
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Abstract

Pan-sharpening algorithms are data-and computation-intensive, and the processing performance can be poor if common serial processing techniques are adopted. This paper presents a parallel computing paradigm for pan-sharpening algorithms based on a generalized fusion model and parallel computing techniques. The developed modules, including eight typical pan-sharpening algorithms, show that the framework can be applied to implement most algorithms. The experiments demonstrate that if parallel strategies are adopted, in the best cases the fastest times required to finish the entire fusion operation (including disk input/output (I/O) and computation) are close to the time required to directly read and write the images without any computation. The parallel processing implemented on a workstation with two CPUs is able to perform these operations up to 13.9 times faster than serial execution. An algorithm in the framework is 32.6 times faster than the corresponding version in the ERDAS IMAGINE software. Additionally, no obvious differences in the fusion effects are observed between the fusion results of different implemented versions. View Full-Text
Keywords: remote sensing; data fusion; pan-sharpening; high performance computing; multi-core computer remote sensing; data fusion; pan-sharpening; high performance computing; multi-core computer
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Yang, J.; Zhang, J.; Huang, G. A Parallel Computing Paradigm for Pan-Sharpening Algorithms of Remotely Sensed Images on a Multi-Core Computer. Remote Sens. 2014, 6, 6039-6063.

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