Reconstructing images corrupted by noise based on D-S evidence theory

被引：6
|
作者：
Zhao, Ye [1 ,2 ]
Mi, Ju-sheng [1 ]
Liu, Xin [3 ]
Sun, Xiao-yun [2 ]
机构：
[1] Hebei Normal Univ, Coll Math & Informat Sci, Shijiazhuang 050016, Hebei, Peoples R China
[2] Shijiazhuang Tie Dao Univ, Dept Math & Phys, Shijiazhuang 050043, Hebei, Peoples R China
[3] Chengde Petr Coll, Dept Math & Phys, Chengde 067000, Hebei, Peoples R China
来源：
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | 2017年 / 8卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Image noise; Evidence theory; D-S rule; DEMPSTER-SHAFER THEORY; CLASSIFICATION; FUSION;
D O I：
10.1007/s13042-015-0353-6
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a new algorithm of noise reduction for image based on evidence theory is proposed. The values of all pixels are restricted in interval [0, 1], and set of data in each column is a term of mass function, which can be calculated by D-S composition rule. Judging noise can be achieved by comparing with the value of pixel in middle and of the current one. The noise will be removed by substituting the current value with value computed. An improved accelerated algorithm is also presented by sample window of 2 x 2. As a measure of conflict K with greater value shows that there would be noises within the current sample window. At last, Experiment image "Lena" with additive noise shows as a test sample, that better result can be achieved with the algorithm.
引用
收藏
页码：611 / 618
页数：8
相关论文
共 50 条
  • [41] Fusion Fingerprint and Face Multi-Biometrics Recognition Based on D-S Evidence Theory
    Wang, Feng
    ADVANCED RESEARCH ON INDUSTRY, INFORMATION SYSTEM AND MATERIAL ENGINEERING, 2012, 459 : 644 - 648
  • [42] Target Recognition Method for Carrier Aircraft Fleet based on Improved D-S Evidence Theory
    Sun, Lifan
    Zou, Jie
    Yang, Zhe
    2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC), 2021, : 3305 - 3310
  • [43] Target recognition decision method based on cloud model and improved D-S evidence theory
    Yin D.
    Huang X.
    Wu Y.
    He Y.
    Xie J.
    Huang, Xiaoying (hjgchxy@163.com), 1600, Chinese Society of Astronautics (42):
  • [44] Research on The Improved Method of D-S Evidence Theory Based on The Fusion of Support and Confidence Entropy
    Yu, Naigong
    Yang, Kang
    Gan, Mengzhe
    2022 IEEE 6TH ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC), 2022, : 1610 - 1615
  • [45] Geometric Hashing classifier based on modified D-S theory in SAR target recognition
    Zhang Jing
    Wang Guohong
    Liang Famai
    Sun Xiaoyan
    PROCEEDINGS OF 2006 CIE INTERNATIONAL CONFERENCE ON RADAR, VOLS 1 AND 2, 2006, : 1458 - +
  • [46] A Trust Evaluation Algorithm for Wireless Sensor Networks Based on Node Behaviors and D-S Evidence Theory
    Feng, Renjian
    Xu, Xiaofeng
    Zhou, Xiang
    Wan, Jiangwen
    SENSORS, 2011, 11 (02) : 1345 - 1360
  • [47] 3D Multi-Object Tracking Based on Dual-Tracker and D-S Evidence Theory
    Ma, Yuanzhi
    Zhang, Jindong
    Qin, Guihe
    Jin, Jingyi
    Zhang, Kunpeng
    Pan, Dongyu
    Chen, Mai
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (03): : 2426 - 2436
  • [48] An Intelligent Complex Event Processing with D-S Evidence Theory in IT Centralized Monitoring
    Cao, Bin
    Li, Jiyun
    INTERNET AND DISTRIBUTED COMPUTING SYSTEMS, IDCS 2013, 2013, 8223 : 373 - 384
  • [49] BER ANALYSIS OF COGNITIVE SIMO NETWORK BASED ON D-S THEORY
    Chang Yuan
    Li Yonghua
    Sun Yanhua
    Lin Jiaru
    2014 4th IEEE International Conference on Network Infrastructure and Digital Content (IEEE IC-NIDC), 2014, : 385 - 389
  • [50] The analog circuit fault diagnosis based on the D-S evidential theory
    Xu, J
    Zhang, XX
    Lv, Q
    ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings, 2005, : 542 - 545
12345