TY - GEN
T1 - Multiview feature selection for very high resolution remote sensing images
AU - Chen, Xi
AU - Li, Hongbo
AU - Gu, Yanfeng
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/22
Y1 - 2014/12/22
N2 - Object based image analysis on very high resolution (VHR) remote sensing imagery often ignores the heterogeneous constitution of feature spaces. In this paper, a supervised multiview feature selection (SMFS) method is proposed. In this method, features are decomposed into multiple disjoint and meaningful feature subsets by employing affinity propagation, where each feature subset represents a view, and each view describes a data characteristic. Features are evaluated and selected within each view. The experimental results on two VHR satellite images, including Quickbird-2 and Worldview-2 images attest to the effectiveness and practicability of the method in compared with traditional single-view algorithms. The results also demonstrate the utility of multiview information in processing VHR datasets.
AB - Object based image analysis on very high resolution (VHR) remote sensing imagery often ignores the heterogeneous constitution of feature spaces. In this paper, a supervised multiview feature selection (SMFS) method is proposed. In this method, features are decomposed into multiple disjoint and meaningful feature subsets by employing affinity propagation, where each feature subset represents a view, and each view describes a data characteristic. Features are evaluated and selected within each view. The experimental results on two VHR satellite images, including Quickbird-2 and Worldview-2 images attest to the effectiveness and practicability of the method in compared with traditional single-view algorithms. The results also demonstrate the utility of multiview information in processing VHR datasets.
KW - affinity propagation
KW - lasso
KW - object based image analysis
KW - supervised multiview feature selection
UR - https://www.scopus.com/pages/publications/84921820881
U2 - 10.1109/IMCCC.2014.116
DO - 10.1109/IMCCC.2014.116
M3 - 会议稿件
AN - SCOPUS:84921820881
T3 - Proceedings - 2014 4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2014
SP - 539
EP - 543
BT - Proceedings - 2014 4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2014
A2 - Li, Jun-Bao
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2014
Y2 - 18 September 2014 through 20 September 2014
ER -