激光与光电子学进展, 2019, 56 (21): 212802, 网络出版: 2019-11-02
基于聚类降维和视觉注意机制的高光谱影像分类 
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Hyperspectral Image Classification Based on Clustering Dimensionality Reduction and Visual Attention Mechanism
图 & 表
图 1. Indian高光谱数据集。(a)伪彩色合成图像;(b)被标记的数据;(c)分类图例
Fig. 1. Indian hyperspectral image dataset. (a) False-color composite imge; (b) labeled data; (c) legends of classification
图 2. Pavia高光谱数据集。(a)伪彩色合成图像;(b)被标记的数据;(c)分类图例
Fig. 2. Pavia hyperspectral image dataset. (a) False-color composite imge; (b) labeled data; (c) legends of classificatin
图 3. 高光谱数据集的波段互信息矩阵。(a) Indian数据集;(b) Pavia数据集
Fig. 3. Band mutual information matrix of hyperspectral datasets. (a) Indian dataset; (b) Pavia dataset
图 4. 单一波段显著性映射结果。(a) Indian数据集优选的波段122及其显著性映射;(b) Indian数据集剔去的波段1及其显著性映射;(c) Pavia数据集优选的波段94及其显著性映射;(d) Pavia数据集剔去的波段1及其显著性映射
Fig. 4. Results of saliency mapping of single band. (a) Band 122 and its saliency mapping selected by Indian dataset; (b) band 1 and its saliency mapping removed by Indian dataset; (c) band 94 and its saliency mapping selected by Pavia dataset; (d) band 1 and its saliency mapping removed by Pavia dataset
表 1Indian数据集上各方法分类精度评价指标对比(黑体表示最优)
Table1. Evaluation indices of classification accuracy of different methods on Indian dataset (best results are highlighted in bold)
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表 2Pavia数据集上各方法分类精度评价指标对比(黑体表示最优)
Table2. Evaluation indices of classification accuracy of different methods on Pavia dataset (best results are highlighted in bold)
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曾朝平, 琚丽君, 张建辰. 基于聚类降维和视觉注意机制的高光谱影像分类[J]. 激光与光电子学进展, 2019, 56(21): 212802. Chaoping Zeng, Lijun Ju, Jianchen Zhang. Hyperspectral Image Classification Based on Clustering Dimensionality Reduction and Visual Attention Mechanism[J]. Laser & Optoelectronics Progress, 2019, 56(21): 212802.
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