TY - GEN
T1 - HYPERSPECTRAL IMAGE CLASSIFICATION BASED ON CLASS CONFUSION MERGING AND SOFT BAND SELECTION
AU - Miao, Xinyuan
AU - Zhang, Ye
AU - Zhang, Junping
AU - Liang, Xuejian
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In hyperspectral image (HSI) classification, the distinction of similar classes has always been a focus of research. In this paper, a new classification module named class confusion merging (CCM) is proposed to improve the classification accuracy, especially for classes with the similar spectral feature. In CCM processing, the merging matrix is firstly constructed based on the confusion matrix to measure the similarity between different classes. Then similar classes are merged as big categories. Finally, for each big category, soft band selection is implemented based on the spectral difference of contained classes for reclassification. To evaluate the performance of CCM, real image experiments are conducted in comparison with no CCM module hyperspectral classification methods. The experiment results demonstrate that the CCM module can improve the classifier performance by providing higher classification accuracy.
AB - In hyperspectral image (HSI) classification, the distinction of similar classes has always been a focus of research. In this paper, a new classification module named class confusion merging (CCM) is proposed to improve the classification accuracy, especially for classes with the similar spectral feature. In CCM processing, the merging matrix is firstly constructed based on the confusion matrix to measure the similarity between different classes. Then similar classes are merged as big categories. Finally, for each big category, soft band selection is implemented based on the spectral difference of contained classes for reclassification. To evaluate the performance of CCM, real image experiments are conducted in comparison with no CCM module hyperspectral classification methods. The experiment results demonstrate that the CCM module can improve the classifier performance by providing higher classification accuracy.
KW - Hyperspectral image classification
KW - Merging matrix
KW - Similar classes
KW - Soft band selection
UR - https://www.scopus.com/pages/publications/85126060982
U2 - 10.1109/IGARSS47720.2021.9553136
DO - 10.1109/IGARSS47720.2021.9553136
M3 - 会议稿件
AN - SCOPUS:85126060982
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3645
EP - 3648
BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Y2 - 12 July 2021 through 16 July 2021
ER -