A novel decision fusion approach to improving classification accuracy of hyperspectral images
A novel decision fusion approach to improving classification accuracy of hyperspectral images
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一种提高高光谱图像分类精度的新型决策融合方法
DOI：
10.1109/igarss.2012.6351696
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Tunc Gormus E
中科院分区：
文献类型：
--
作者：
Tunc Gormus E
本文将离散小波变换(DWT)和经验模式分解(EMD)作为多分类器与决策融合系统的预处理阶段。该方法由三个步骤组成。在第一步中，对每个高光谱图像波段进行2D-EMD，以获得有用的空间信息。然后，通过对2D-EMD执行的频带的每个签名应用1D-DWT来获得有用的光谱信息。利用光谱信息和空间信息生成一种新的特征集。第二步，利用支持向量机对每个特征进行独立分类，形成一个多分类器系统。在最后一步中，使用决策融合准则对分类结果进行融合以产生一个最终分类。与独立分类器相比，该方法在减少特征数量的情况下，提高了整体分类精度。
In this paper discrete wavelet transform (DWT) and empirical mode decomposition (EMD) are employed as a preprocessing stage in a multiclassifier and decision fusion system. The proposed method consists of three steps. In the first step, 2D-EMD is performed on each hyperspectral image band in order to obtain useful spatial information. Then, useful spectral information is obtained by applying the 1D-DWT to each signature of 2D-EMD performed bands. A novel feature set is generated using both spectral and spatial information. In the second step, each feature is independently classified by support vector machines (SVM), creating a multiclassifier system. In the last step, classification results are fused using a decision fusion criterion to produce one final classification. The proposed method improves overall classification accuracy over independent classifiers when reduced number of features are employed.
DOI：
10.1098/rspa.1998.0193
发表时间：
1998-03-08
影响因子：
3.5
作者：
Huang, NE;Shen, Z;Liu, HH
通讯作者：
Liu, HH
用于光谱分析的高光谱图像可视化
DOI：
--
发表时间：
2004
期刊：
影响因子：
--
作者：
P. Hsu;Y. Tseng
通讯作者：
Y. Tseng