Exploration of the influence of ambiguity pixels on image classification reliability

被引:0
|
作者
Xu, Hui [1 ]
Zhang, Penglin [1 ]
机构
[1] Wuhan Univ, Sch Remote Sensing & Informat Engn, 129 LuoYu Rd, Wuhan, Peoples R China
关键词
Ambiguity pixels; Image classification; Reliability; Unambiguity pixels;
D O I
10.1007/s12517-020-05825-6
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Ambiguity pixels and unreliable classification are easily generated in remote sensing images (RSIs) due to the complexity of landscape sand imaging conditions. At present, few studies focus on the quantification, influence, and propagation mechanism of ambiguity pixels in RSI classification. To investigate these problems, this paper extracts the ambiguity pixels in the image, and explores their influence on classification reliability. First, the pixels of an RSI are classified into ambiguity and unambiguity classes on the basis of uncertainty. Second, the reliability of classification results on ambiguity and unambiguity pixels is evaluated and analyzed using defined reliability indices. Finally, three experiments are designed to reveal the influence of ambiguity pixels on the reliability of RSI classification. Experimental results show that the indicator values of the unambiguity pixels are much higher than those of the ambiguity pixels, illustrating the effects of ambiguity pixels on the reliability of RSI classification results.
引用
收藏
页数:11
相关论文
共 50 条
  • [31] Enhancing the reliability of image classification using the intrinsic features
    Lu, Zhenyu
    Lu, Yonggang
    KNOWLEDGE-BASED SYSTEMS, 2023, 263
  • [32] FRIENDSHIP - AN EXPLORATION AND APPRECIATION OF AMBIGUITY
    BRISSETT, D
    OLDENBURG, R
    PSYCHIATRY-INTERPERSONAL AND BIOLOGICAL PROCESSES, 1982, 45 (04): : 325 - 335
  • [33] Improved hyperspectral image classification by active learning using pre-designed mixed pixels
    Samat, Alim
    Li, Jun
    Liu, Sicong
    Du, Peijun
    Miao, Zelang
    Luo, Jieqiong
    PATTERN RECOGNITION, 2016, 51 : 43 - 58
  • [34] Automating image classification, a preliminary foray using archival GIS data to label pixels.
    Fegan, M
    Devonport, C
    Ahmad, W
    IGARSS 2001: SCANNING THE PRESENT AND RESOLVING THE FUTURE, VOLS 1-7, PROCEEDINGS, 2001, : 1886 - 1888
  • [35] A Novel Method for Hyperspectral Image Classification Based on Laplacian Eigenmap Pixels Distribution-Flow
    Hou, Biao
    Zhang, Xiangrong
    Ye, Qiang
    Zheng, Yaoguo
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2013, 6 (03) : 1602 - 1618
  • [36] IMAGE-BASED BUILDING CLASSIFICATION AND 3D MODELING WITH SUPER-PIXELS
    Kluckner, Stefan
    Bischof, Horst
    PCV 2010 - PHOTOGRAMMETRIC COMPUTER VISION AND IMAGE ANALYSIS, PT I, 2010, 38 : 233 - 238
  • [37] Data Exploration and Classification of News Article Reliability: Deep Learning Study
    Zhan, Kevin
    Li, Yutong
    Osmani, Rafay
    Wang, Xiaoyu
    Cao, Bo
    JMIR INFODEMIOLOGY, 2022, 2 (02):
  • [38] The Reliability of GPS Ambiguity Resolution
    Teunissen, Peter J. G.
    Joosten, Peter
    Odijk, Dennis
    GPS SOLUTIONS, 1999, 2 (03) : 63 - 69
  • [39] RELIABILITY, AMBIGUITY AND CONTENT ANALYSIS
    SCHUTZ, WC
    PSYCHOLOGICAL REVIEW, 1952, 59 (02) : 119 - 129
  • [40] The Reliability of GPS Ambiguity Resolution
    Peter J. G. Teunissen
    Peter Joosten
    Dennis Odijk
    GPS Solutions, 1999, 2 : 63 - 69