PROBABILITY FUSION FOR HYPERSPECTRAL AND LIDAR DATA

被引：0
|
作者：
Ge, Chiru [1 ]
Du, Qian [2 ]
机构：
[1] Shandong Normal Univ, Informat Sci & Engn, Jinan 250358, Peoples R China
[2] Mississippi State Univ, Elect & Comp Engn, Starkville, MS 39762 USA
来源：
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年
基金：
国家重点研发计划;
关键词：
Hyperspectral image; LiDAR; residual fusion; classification; probability fusion; CLASSIFICATION;
D O I：
10.1109/IGARSS39084.2020.9323750
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a new probability fusion strategy is proposed for hyperspectral and LiDAR data classification, which is inspired by the representation residual fusion strategy in our previous work. Unlike the residual fusion strategy utilizes a collaborative representation classifier, the probability fusion strategy deploys a deep residual network (DRN). This paper compares the two fusion strategies. The experiment results show that the probability fusion strategy with DRN is better than the residual fusion strategy in classification performance.
引用
收藏
页码：2675 / 2678
页数：4
相关论文
共 50 条
  • [41] Information Fusion for Classification of Hyperspectral and LiDAR Data Using IP-CNN
    Zhang, Mengmeng
    Li, Wei
    Tao, Ran
    Li, Hengchao
    Du, Qian
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [42] FEATURE FUSION OF HYPERSPECTRAL AND LIDAR DATA USING EXTINCTION PROFILES AND TOTAL VARIATION
    Ghamisi, Pedram
    Rasti, Behnood
    Zhu, Xiao X.
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 2621 - 2624
  • [43] OBJECT-BASED FUSION OF HYPERSPECTRAL AND LIDAR DATA FOR CLASSIFICATION OF URBAN AREAS
    Marpu, Prashanth Reddy
    Martinez, Sergio Sanchez
    2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2015,
  • [44] Multiple Information Collaborative Fusion Network for Joint Classification of Hyperspectral and LiDAR Data
    Tang, Xu
    Zou, Yizhou
    Ma, Jingjing
    Zhang, Xiangrong
    Liu, Fang
    Jiao, Licheng
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62
  • [45] URBAN AREA OBJECT-BASED CLASSIFICATION BY FUSION OF HYPERSPECTRAL AND LIDAR DATA
    Kiani, Kamel
    Mojaradi, Barat
    Esmaeily, Ali
    Salehi, Bahram
    2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014,
  • [46] Fusion of hyperspectral and LIDAR remote sensing data for classification of complex forest areas
    Dalponte, Michele
    Bruzzone, Lorenzo
    Gianelle, Damiano
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2008, 46 (05): : 1416 - 1427
  • [47] Urban classification by multi-feature fusion of hyperspectral image and LiDAR data
    Cao Q.
    Ma A.
    Zhong Y.
    Zhao J.
    Zhao B.
    Zhang L.
    Yaogan Xuebao/Journal of Remote Sensing, 2019, 23 (05): : 892 - 903
  • [48] MULTI-SCALE FEATURE FUSION FOR HYPERSPECTRAL AND LIDAR DATA JOINT CLASSIFICATION
    Zhang, Maqun
    Gao, Feng
    Dong, Junyu
    Qi, Lin
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 2856 - 2859
  • [49] Mapping biomass and stress in the Sierra Nevada using lidar and hyperspectral data fusion
    Swatantran, Anu
    Dubayah, Ralph
    Roberts, Dar
    Hofton, Michelle
    Blair, J. Bryan
    REMOTE SENSING OF ENVIRONMENT, 2011, 115 (11) : 2917 - 2930
  • [50] Fusion of Multispectral LiDAR, Hyperspectral, and RGB Data for Urban Land Cover Classification
    Haensch, Ronny
    Hellwich, Olaf
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 18 (02) : 366 - 370
12345