Adaptive frequency median filter for the salt and pepper denoising problem

被引:58
作者
Erkan, Ugur [1 ]
Enginoglu, Serdar [2 ]
Thanh, Dang N. H. [3 ,5 ]
Le Minh Hieu [4 ]
机构
[1] Karamanoglu Mehmetbey Univ, Engn Fac, Comp Engn, Karaman, Turkey
[2] Canakkale Onsekiz Mart Univ, Fac Arts & Sci, Dept Math, Canakkale, Turkey
[3] Hue Coll Ind, Dept Informat Technol, Hue, Vietnam
[4] Univ Econ, Univ Danang, Dept Econ, Danang, Vietnam
[5] Univ Econ Ho Chi Minh City, Sch Business Informat Technol, Dept Informat Technol, Ho Chi Minh City, Vietnam
关键词
adaptive filters; image denoising; median filters; adaptive frequency median filter; pepper denoising problem; AFMF; pepper noise; adaptive condition; adaptive median filter; AMF; original grey value; NOISE; REMOVAL; ALGORITHM; DENSITY;
D O I
10.1049/iet-ipr.2019.0398
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 article, the authors propose an adaptive frequency median filter (AFMF) to remove the salt and pepper noise. AFMF uses the same adaptive condition of adaptive median filter (AMF). However, AFMF employs frequency median to restore grey values of the corrupted pixels instead of the median of AMF. The frequency median can exclude noisy pixels from evaluating a grey value of the centre pixel of the considered window, and it focuses on the uniqueness of grey values. Hence, the frequency median produces a grey value closer to the original grey value than the one by the median of AMF. Therefore, AFMF outperforms AMF. In experiments, the authors tested the proposed method on a variety of natural images of the MATLAB library, as well as the TESTIMAGES data set. Additionally, they also compared the denoising results of AFMF to the ones of other state-of-the-art denoising methods. The results showed that AFMF denoises more effectively than other methods.
引用
收藏
页码:1291 / 1302
页数:12
相关论文
共 47 条
  • [1] Aggarwal H. K., 2014, PROC INDIAN C COMPUT, P1
  • [2] [Anonymous], 1977, EXPLORATORY DATA ANA
  • [3] Asuni N., 2014, P IT CHAPT C 2014 SM
  • [4] Detail-preserving switching algorithm for the removal of random-valued impulse noise
    Azhar, Marium
    Dawood, Hassan
    Dawood, Hussain
    Choudhary, Gulraiz Iqbal
    Bashir, Ali Kashif
    Chauhdary, Sajjad Hussain
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2019, 10 (10) : 3925 - 3945
  • [5] THE WEIGHTED MEDIAN FILTER
    BROWNRIGG, DRK
    [J]. COMMUNICATIONS OF THE ACM, 1984, 27 (08) : 807 - 818
  • [6] Chang J.R., 2014, FUTUR INF TECHNOL LE, V309, P713
  • [7] Adaptive probability filter for removing salt and pepper noises
    Chen, Jiayi
    Zhan, Yinwei
    Cao, Huiying
    Wu, Xingda
    [J]. IET IMAGE PROCESSING, 2018, 12 (06) : 863 - 871
  • [8] Effective and adaptive algorithm for pepper-and-salt noise removal
    Chen, Qing-Qiang
    Hung, Mao-Hsiung
    Zou, Fumin
    [J]. IET IMAGE PROCESSING, 2017, 11 (09) : 709 - 716
  • [9] Adaptive impulse detection using center-weighted median filters
    Chen, T
    Wu, HR
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2001, 8 (01) : 1 - 3
  • [10] Algorithms and software for total variation image reconstruction via first-order methods
    Dahl, Joachim
    Hansen, Per Christian
    Jensen, Soren Holdt
    Jensen, Tobias Lindstrom
    [J]. NUMERICAL ALGORITHMS, 2010, 53 (01) : 67 - 92