Hyperspectral Ratio Feature Selection: Agricultural Product Inspection Example

机译：高光谱比率特征选择：农产品检验例

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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：我们描述了一种快速减少和特征选择的快速方法，用于在高光谱数据中分类的比率特征。选择的案例研究是区分常规血栓螺母。对于这种情况，我们发现，使用多个波段中的响应的比率提供比波段响应子集更好的特征。我们发现，使用欧几里德最小距离度量的使用比最近邻分类器中的更传统的光谱角映射距离度量略微更好地产生略微更好的结果。

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《Conference on Nondestructive Sensing for Food Safety, Quality, and Natural Resources》|2004年||共11页
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Songyot Nakariyakul; David Casasent;
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正文语种
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;产品检查;

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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 Nondestructive Sensing for Food Safety, Quality, and Natural Resources . 2004

机译：高光谱比特征选择：农产品检验实例
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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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