Subsurface linear unmixing on a controlled underwater enviroment

E. Carpena-Colon, Luis O. Jimenez-Rodriguez, Emmanuel Arzuaga, M. Velez-Reyes
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Abstract

This paper presents the development and enhancement of a subsurface (underwater) linear unmixing algorithm, called LIGU, specially conceived to determine individual contributions to the measured signal of given spectral reflectance of objects at the bottom of coastal shallow waters. This algorithm is part of a Hyperspectral Coastal Image Analysis Toolbox (HyCIAT), which is a repository of tools to be used to retrieve information from object embedded in a diffusive and murky medium. This paper discusses mathematical formulations behind the subsurface unmixing algorithm LIGU and presents enhancements made to the algorithm. Finally, quantitative and qualitative results will be presented using a hyperspectral data set from a controlled and well known environment. These results provide noticeable quantitative improvement when LIGU is compared with other linear unmixing algorithm not developed for subsurface (underwater) applications.
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在受控的水下环境下进行地下线性分解
本文介绍了一种称为LIGU的地下(水下)线性解混算法的发展和增强,该算法专门用于确定沿海浅水底部物体的给定光谱反射率对测量信号的个体贡献。该算法是高光谱海岸图像分析工具箱(HyCIAT)的一部分,HyCIAT是一个工具库,用于从嵌入在扩散和模糊介质中的物体中检索信息。本文讨论了地下分解算法LIGU背后的数学公式,并对该算法进行了改进。最后,定量和定性结果将使用来自受控和众所周知的环境的高光谱数据集。与其他未开发用于地下(水下)应用的线性解混算法相比,这些结果提供了显著的定量改进。
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