Using Wavelet Support Vector Machine for Classification of Hyperspectral Images

被引：2
|
作者：
Banki, Mohammad Hossein [1 ]
Shirazi, Ali Asghar Beheshti [1 ]
机构：
[1] Iran Univ Sci & Technol, Dept Elect Engn, Tehran, Iran
来源：
2009 SECOND INTERNATIONAL CONFERENCE ON MACHINE VISION, PROCEEDINGS, ( ICMV 2009) | 2009年
关键词：
Hyperspectral image processing; Classification; SVM; Wavelet Kernel;
D O I：
10.1109/ICMV.2009.64
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Support Vector Machine (SVM) is a machine learning algorithm, which has been used recently for classification of hyperspectral images. SVM uses various kernel functions like RBF and polynomial to map the data into higher dimensional space to improve data separability. New kernel functions are used in this paper to classify hyperspectral images which are based on wavelet functions as named Wavelet-kernels. The experimental results indicate that Wavelet-kernels provide better classification accuracy than previous kernels.
引用
收藏
页码：154 / 157
页数：4
相关论文
共 50 条
  • [1] Classification of Hyperspectral Images Using Unsupervised Support Vector Machine
    Adibi, Sayyed Ashkan
    Hassani, Mohammad
    Karami, Azam
    [J]. IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XXIII, 2017, 10427
  • [2] Wavelet denoising before support vector classification of hyperspectral images
    Demir, Beguem
    Ertuerk, Sarp
    [J]. 2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1-3, 2007, : 1009 - 1012
  • [3] Feature weighting algorithms for classification of hyperspectral images using a support vector machine
    Qi, Bin
    Zhao, Chunhui
    Yin, Guisheng
    [J]. APPLIED OPTICS, 2014, 53 (13) : 2839 - 2846
  • [4] Hyperspectral image classification using Support Vector Machine
    Moughal, T. A.
    [J]. 6TH VACUUM AND SURFACE SCIENCES CONFERENCE OF ASIA AND AUSTRALIA (VASSCAA-6), 2013, 439
  • [5] Classification of hyperspectral data using support vector machine
    Zhang, JP
    Zhang, Y
    Zhou, TX
    [J]. 2001 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL I, PROCEEDINGS, 2001, : 882 - 885
  • [6] Deep proximal support vector machine classifiers for hyperspectral images classification
    Ganesan Kalaiarasi
    Sureshbabu Maheswari
    [J]. Neural Computing and Applications, 2021, 33 : 13391 - 13415
  • [7] Deep proximal support vector machine classifiers for hyperspectral images classification
    Kalaiarasi, Ganesan
    Maheswari, Sureshbabu
    [J]. NEURAL COMPUTING & APPLICATIONS, 2021, 33 (20): : 13391 - 13415
  • [8] Feature Generation of Hyperspectral Images for Fuzzy Support Vector Machine Classification
    Shen, Yi
    He, Zhi
    Wang, Qiang
    Wang, Yan
    [J]. 2012 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC), 2012, : 1977 - 1982
  • [9] Empirical Mode Decomposition of Hyperspectral Images for Support Vector Machine Classification
    Demir, Begum
    Erturk, Sarp
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2010, 48 (11): : 4071 - 4084
  • [10] Classification of Hyperspectral Images using Edge Preserving Filter and Nonlinear Support Vector Machine (SVM)
    Perisetty, Abhilash
    Shaik, Parvez Rahaman
    Bodempudi, Sai Teja
    Kumar, B. L. N. Phaneendra
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS 2020), 2020, : 1050 - 1054
12345