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Speeding up the MATLAB Hyperspectral Image Analysis Toolbox using GPUs and the Jacket Toolbox

机译:使用GPU和夹套工具箱加速MATLAB高光谱图像分析工具箱

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The Hyperspectral Image Analysis Toolbox (HIAT) is a MATLAB toolbox for the analysis of hyperspectral imagery. HIAT includes a collection of algorithms for processing of hyperspectral and multispectral imagery under the MATLAB environment. The objective of HIAT is to provide a suite of information extraction algorithms to users of hyperspectral and multispectral imagery across different application domains. HIAT has been developed as part of the NSF Bernard M. Gordon Center for Subsurface Sensing and Imaging Solutionware that seeks to develop a repository of reliable and reusable software tools that can be shared by researchers across research domains. HIAT includes feature extraction and selection, supervised and unsupervised classification algorithms, unmixing, and visualization algorithms developed at the UPRM Laboratory for Applied Remote Sensing and Image Processing. A key limitation of the MATLAB environment is its difficulty in managing large images. Here we investigate the use of the recently released MATLAB Jacket Toolbox that allows implementation of MATLAB programs in GPUs. This paper presents a comparison of the CPU implementation with the GPU implementation of different routines of HIAT.
机译:高光谱图像分析工具箱(Hiat)是MATLAB工具箱,用于分析高光谱图像。 Hiat包括用于在Matlab环境下处理高光谱和多光谱图像的算法集合。 HIAT的目标是向不同应用领域的超光谱和多光谱图像提供一套信息提取算法。 HIAT已作为NSF Bernard M. Gordon中心的部分地下传感和成像解决方案开发,寻求开发可通过研究领域的研究人员共享的可靠和可重复使用的软件工具的存储库。 HIAI包括在UPRM实验室开发的特征提取和选择,监督和无监督的分类算法,在UPRM实验室进行遥感和图像处理。 MATLAB环境的关键限制是管理大图像的困难。在这里,我们调查了最近发布的MATLAB夹克工具箱的使用,允许在GPU中实现MATLAB程序。本文介绍了CPU实现与HPU实施的不同例程的GPU实现。

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