Classification method of CO2 hyperspectral remote sensing data based on neural network

被引：11
|
作者：
Zhang, Le [1 ,2 ]
Wang, Jinsong [2 ]
An, Zhiyong [2 ]
机构：
[1] Shenyang Ligong Univ, Equipment Engn Dept, Shenyang 100168, Peoples R China
[2] Changchun Univ Sci & Technol, Optoelect Engn Dept, Changchun 130022, Jilin, Peoples R China
来源：
COMPUTER COMMUNICATIONS | 2020年 / 156卷
关键词：
Hyperspectral; Remote sensing image; Neural network; Carbon dioxide; Support vector machine;
D O I：
10.1016/j.comcom.2020.03.045
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Based on the dimension reduction of hyperspectral remote sensing image, a new neural network method is used to classify the hyperspectral remote sensing image of carbon dioxide in detail. Firstly, the Kernel Principal Component Analysis (KPCA) and Genetic Algorithms (GA) are used to reduce the dimension of hyperspectral remote sensing images; secondly, the traditional remote sensing image classification methods (ISODATA, SVM), traditional neural networks (BP), and new neural networks are used to classify the hyperspectral remote sensing images. Finally, noise assessment method based on local mean and local standard deviation (LMLSD) of spectral image is used to evaluate the classification accuracy. In addition, hyperspectral remote sensing images are dimensionality reduction. Secondly, the comparison between the traditional remote sensing image classification method and the new neural network method is analyzed. Finally, a new neural network method is applied to classify hyperspectral remote sensing images.
引用
收藏
页码：124 / 130
页数：7
相关论文
共 50 条
  • [21] WEED CLASSIFICATION IN HYPERSPECTRAL REMOTE SENSING IMAGES VIA DEEP CONVOLUTIONAL NEURAL NETWORK
    Farooq, Adnan
    Hu, Jiankun
    Jia, Xiuping
    IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 3816 - 3819
  • [22] Edge protection filtering and convolutional neural network for hyperspectral remote sensing image classification
    Lv, Huanhuan
    Wang, Zhuolu
    Zhang, Hui
    INFRARED PHYSICS & TECHNOLOGY, 2022, 122
  • [23] Multiscale Feature Aggregation Capsule Neural Network for Hyperspectral Remote Sensing Image Classification
    Lei, Runmin
    Zhang, Chunju
    Zhang, Xueying
    Huang, Jianwei
    Li, Zhenxuan
    Liu, Wencong
    Cui, Hao
    REMOTE SENSING, 2022, 14 (07)
  • [24] Effect of pooling strategy on convolutional neural network for classification of hyperspectral remote sensing images
    Bera, Somenath
    Shrivastava, Vimal K.
    IET IMAGE PROCESSING, 2020, 14 (03) : 480 - 486
  • [25] An efficient radial basis function neural network for hyperspectral remote sensing image classification
    Jiaojiao Li
    Qian Du
    Yunsong Li
    Soft Computing, 2016, 20 : 4753 - 4759
  • [26] An Adaptive Capsule Network for Hyperspectral Remote Sensing Classification
    Ding, Xiaohui
    Li, Yong
    Yang, Ji
    Li, Huapeng
    Liu, Lingjia
    Liu, Yangxiaoyue
    Zhang, Ce
    REMOTE SENSING, 2021, 13 (13)
  • [27] Hyperspectral Remote Sensing Images Classification Method Based on Learned Dictionary
    Li, Min
    Shen, Jun
    Jiang, Lianjun
    PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND COMPUTER APPLICATIONS (ICSA 2013), 2013, 92 : 357 - 362
  • [28] Remote sensing image classification method based on improved ShuffleNet convolutional neural network
    Li, Ziqi
    Su, Yuxuan
    Zhang, Yonghong
    Yin, Hefeng
    Sun, Jun
    Wu, Xiaojun
    INTELLIGENT DATA ANALYSIS, 2024, 28 (02) : 397 - 414
  • [29] An efficient radial basis function neural network for hyperspectral remote sensing image classification
    Li, Jiaojiao
    Du, Qian
    Li, Yunsong
    SOFT COMPUTING, 2016, 20 (12) : 4753 - 4759
  • [30] Remote sensing image classification method using neural network based on generalized image
    Peng, TQ
    Li, BC
    IMAGE PROCESSING AND PATTERN RECOGNITION IN REMOTE SENSING, 2003, 4898 : 44 - 48
12345