Comparison of unsupervised band selection methods for hyperspectral imaging

被引：0
|
作者：
Martinez-Uso, Adolfo [1 ]
Pla, Filiberto [1 ]
Sotoca, Jose M. [1 ]
Garcia-Sevilla, Pedro [1 ]
机构：
[1] Jaume I Univ, Dept Lenguajes & Sistemas Informat, Campus Riu Sec S-N, Castellon de La Plana 12071, Spain
来源：
PATTERN RECOGNITION AND IMAGE ANALYSIS, PT 1, PROCEEDINGS | 2007年 / 4477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：
Different methods have been proposed in order to deal with the huge amount of information that hyperspectral applications involve. This paper presents a comparison of some of the methods proposed for band selection. A relevant and recent set of methods have been selected that cover the main tendencies in this field. Moreover, a variant of an existing method is also introduced in this work. The comparison criterion used is based on pixel classification tasks.
引用
收藏
页码：30 / +
页数：3
相关论文
共 50 条
  • [21] Summarization of Band Selection Methods For Hyperspectral Images
    Chopra, Jatin
    Sehgal, Smriti
    2021 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2021), 2021, : 348 - 354
  • [22] Hyperspectral interventional imaging for enhanced tissue visualization and discrimination combining band selection methods
    Dorra Nouri
    Yves Lucas
    Sylvie Treuillet
    International Journal of Computer Assisted Radiology and Surgery, 2016, 11 : 2185 - 2197
  • [23] Hyperspectral interventional imaging for enhanced tissue visualization and discrimination combining band selection methods
    Nouri, Dorra
    Lucas, Yves
    Treuillet, Sylvie
    INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2016, 11 (12) : 2185 - 2197
  • [24] Combination of Clustering and Ranking Techniques for Unsupervised Band Selection of Hyperspectral Images
    Datta, Aloke
    Ghosh, Susmita
    Ghosh, Ashish
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 8 (06) : 2814 - 2823
  • [25] Unsupervised Hyperspectral Band Selection via Hybrid Graph Convolutional Network
    Yu, Chunyan
    Zhou, Sijia
    Song, Meiping
    Gong, Baoyu
    Zhao, Enyu
    Chang, Chein-, I
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [26] Similarity-Based Unsupervised Band Selection for Hyperspectral Image Analysis
    Du, Qian
    Yang, He
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2008, 5 (04) : 564 - 568
  • [27] Unsupervised Hyperspectral Band Selection by Fuzzy Clustering With Particle Swarm Optimization
    Zhang, Mingyang
    Ma, Jingjing
    Gong, Maoguo
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 14 (05) : 773 - 777
  • [28] Unsupervised Cluster-based Band Selection for Hyperspectral Image Classification
    Wu, Jee-Cheng
    Tsuei, Gwo-Chyang
    PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND ELECTRONICS INFORMATION (ICACSEI 2013), 2013, 41 : 562 - 565
  • [29] Superpixel-Based Unsupervised Band Selection for Classification of Hyperspectral Images
    Yang, Chen
    Bruzzone, Lorenzo
    Zhao, Haishi
    Tan, Yulei
    Guan, Renchu
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2018, 56 (12): : 7230 - 7245
  • [30] Stochastic gate-based autoencoder for unsupervised hyperspectral band selection
    Sun, He
    Zhang, Lei
    Wang, Lizhi
    Huang, Hua
    PATTERN RECOGNITION, 2022, 132
12345