A GA-based feature selection algorithm for remote sensing images

被引：0
|
作者：
De Stefano, C. [1 ]
Fontanella, F. [1 ]
Marrocco, C. [1 ]
机构：
[1] Univ Cassino, Dipartimento Automaz Elettron Ingn Informaz & Mat, I-02043 Cassino, FR, Italy
来源：
APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS | 2008年 / 4974卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a GA-based feature selection algorithm in which feature subsets are evaluated by means of a separability index. This index is based on a filter method, which allows to estimate statistical properties of the data, independently of the classifier used. More specifically, the defined index uses covariance matrices for evaluating how spread out the probability distributions of data are in a given n-dimensional space. The effectiveness of the approach has been tested on two satellite images and the results have been compared with those obtained without feature selection and with those obtained by using a previously developed CA-based feature selection algorithm.
引用
收藏
页码：285 / 294
页数：10
相关论文
共 50 条
  • [1] GeneSIS: A GA-based fuzzy segmentation algorithm for remote sensing images
    Mylonas, Stelios K.
    Stavrakoudis, Dimitris G.
    Theocharis, John B.
    [J]. KNOWLEDGE-BASED SYSTEMS, 2013, 54 : 86 - 102
  • [2] PSO- and GA-Based Hybrid Algorithm for Feature Selection
    Kumar, S. Sandeep
    Sai, N. Raghavendra
    Kumar, M. Jogendra
    [J]. PROCEEDINGS OF SECOND INTERNATIONAL CONFERENCE ON SUSTAINABLE EXPERT SYSTEMS (ICSES 2021), 2022, 351 : 475 - 484
  • [3] A Ga-based negative selection algorithm
    Gao, Xiao-Zhi
    Ovaska, Seppo Jari
    Wang, Xiaolei
    [J]. INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2008, 4 (04): : 971 - 979
  • [4] A GA-based Sequential Fuzzy Segmentation Approach For Classification of Remote Sensing Images
    Mylonas, Stelios K.
    Stavrakoudis, Dimitris G.
    Theocharis, John B.
    [J]. 2012 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2012,
  • [5] Feature selection and classification based on ant colony algorithm for hyperspectral remote sensing images
    Zhou, Shuang
    Zhang, Jun-ping
    Su, Bao-ku
    [J]. PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 1046 - +
  • [6] Feature selection for modular GA-based classification
    Zhu, FM
    Guan, S
    [J]. APPLIED SOFT COMPUTING, 2004, 4 (04) : 381 - 393
  • [7] A new search algorithm for feature selection in hyperspectral remote sensing images
    Serpico, SB
    Bruzzone, L
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2001, 39 (07): : 1360 - 1367
  • [8] GA-based feature subset selection for myoelectric classification
    Oskoei, Mohammadreza Asghari
    Hu, Huosheng
    [J]. 2006 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, VOLS 1-3, 2006, : 1465 - +
  • [9] A HYBRID METHOD FOR INTRUSION DETECTION WITH GA-BASED FEATURE SELECTION
    Chen, Zh-Xian
    Huang, Hao
    [J]. INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2011, 17 (02): : 175 - 186
  • [10] Feature selection method of remote sensing data based on physicomimetics algorithm
    Wei, Fangjie
    Wang, Liguo
    [J]. INFORMATION SCIENCE AND MANAGEMENT ENGINEERING, VOLS 1-3, 2014, 46 : 279 - 286
12345