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| 高光谱遥感影像波段选择算法评价方法研究 | |
| 引用本文： | 李行,毛定山,张连蓬.高光谱遥感影像波段选择算法评价方法研究[J].地理与地理信息科学,2006,22(6):34-37. |
| 作者姓名： | 李行 毛定山 张连蓬 |
| 作者单位： | 1. 华东师范大学河口海岸学国家重点实验室,上海,200062 2. 山东科技大学信息科学与工程学院,山东,青岛,266510;中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京,100101 3. 徐州师范大学测绘学院,江苏,徐州,221116 |
| 基金项目： | 国家自然科学基金;国家重点基础研究发展计划(973计划) |
| 摘 要： | 波段选择在高光谱影像数据降维处理中尤为重要，其算法较多，但针对波段选择算法评价方法的研究却很少。该文提出一种波段选择算法的评价方法。引入信息量、类别可分性和相关性3个指标，对所选波段子集进行度量，通过比较不同波段选择算法所选波段子集的度量结果，实现对波段选择算法的评价。在试验中，将该评价方法应用于4种常用的波段选择算法，分析了评价结果并验证了该评价方法的可行性。 |
| 关 键 词： | 高光谱影像 波段选择算法 评价方法 |
| 文章编号： | 1672-0504(2006)06-0034-04 |
| 收稿时间： | 2006-05-25 |
| 修稿时间： | 2006-08-08 |
Evaluation Method for Band Selection Algorithm of Hyperspectral Image |
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| LI Xing,MAO Ding-shan,ZHANG Lian-peng.Evaluation Method for Band Selection Algorithm of Hyperspectral Image[J].Geography and Geo-Information Science,2006,22(6):34-37. | |
| Authors: | LI Xing MAO Ding-shan ZHANG Lian-peng |
| Affiliation: | 1 . State Key Laboratory of Estuarine and Coastal Research, East China Norvnal University, Shanghai 200062;2. College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao 266510 ; 3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101; 4. School of Geodesy and Geomatics , Xuzhou ,Normal University , Xuzhou 221116, China |
| Abstract: | As a dimersionality reduction method, band selection is a significant preprocessing step used for classification applications of hyperspectral image data. And a large number of algorithms have been proposed for band selection. However, the evaluation method for band selection algorithms was rarely studied. In order to evaluate the performance of band selection algorithms, an evaluation method is proposed. The method is implemented by measuring the selected band sets from three aspects, i. e. , information content, class separability and correlation. In experiment, the evaluation method is applied to four common band selections algorithms. The results of experiments show that the evaluation method is feasible in practical applications. |
| Keywords: | hyperspectral image band selection algorithm evaluation method |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
