Hyperspectral Ratio Feature Selection: Agricultural Product Inspection Example

机译：高光谱比特征选择：农产品检验实例

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We describe a fast method for dimensionality reduction and feature selection of ratio features for classification in hyperspectral data. The case study chosen is to discriminate internally damaged almond nuts from normal ones. For this case study, we find that using the ratios of the responses in several wavebands provides better features than a subset of waveband responses. We find that use of the Euclidean Minimum Distance metric gives slightly better results than the more conventional Spectral Angle Mapper distance metric in a nearest neighbor classifier.

机译：我们描述了一种用于降维和比率特征的特征选择的快速方法，用于在高光谱数据中进行分类。选择的案例研究是将内部损坏的杏仁坚果与普通的坚果区别开来。对于本案例研究，我们发现使用几个波段的响应比率比波段响应的子集提供更好的功能。我们发现，在最近邻分类器中，与更常规的“光谱角度映射器”距离度量标准相比，使用“欧式最小距离”度量标准可获得更好的结果。

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《Nondestructive Sensing for Food Safety, Quality, and Natural Resources》|2004年|P.133-143|共11页
会议地点 PhiladelphiaPA (US)
作者
Songyot Nakariyakul; David Casasent;
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作者单位

Department of Electrical Computer Engineering Carnegie Mellon University, Pittsburgh, PA 15213;

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会议组织
原文格式 PDF
正文语种 eng
中图分类食品标准与检验;
关键词
feature selection; hyperspectral data; product inspection;

机译：特征选择;高光谱数据;产品检验;

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1. Calibration of a pushbroom hyperspectral imaging system for agricultural inspection [J] . K. C. Lawrence, B. Park, W. R. Windham, Transactions of the ASABE . 2003,第2期

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2. Feature-selection ability of the decision-tree algorithm and the impact of feature-selection/extraction on decision-tree results based on hyperspectral data [J] . Y. Y. WANG, J. LI International journal of remote sensing . 2008,第10期

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3. A Fast Clonal Selection Algorithm for Feature Selection in Hyperspectral Imagery [J] . ZHONG Yanfei, ZHANG Liangpei 地球空间信息科学学报：英文版 . 2009,第003期

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4. Hyperspectral Ratio Feature Selection: Agricultural Product Inspection Example [C] . Songyot Nakariyakul, David Casasent Conference on Nondestructive Sensing for Food Safety, Quality, and Natural Resources . 2004

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5. Feature selection algorithms for anomaly detection in hyperspectral data. [D] . Nakariyakul, Songyot. 2007

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6. Classification of Aflatoxin B1 Concentration of Single Maize Kernel Based on Near-Infrared Hyperspectral Imaging and Feature Selection [O] . Quan Zhou, Wenqian Huang, Dong Liang, 2021

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7. Hyperspectral Ratio Feature Selection: Agricultural Product Inspection Example [O] . Songyot Nakariyakul, David Casasent 2008

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8. Improved Feature Extraction, Feature Selection, and Identification Techniques That Create a Fast Unsupervised Hyperspectral Target Detection Algorithm [R] . Johnson, R. J. 2008

机译：改进的特征提取，特征选择和识别技术，创建快速无监督的高光谱目标检测算法

Hyperspectral Ratio Feature Selection: Agricultural Product Inspection Example

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