Image Denoising Using Orthogonal Spline

被引：0
|
作者：
Zhou, Kaiting [1 ]
Zheng, Lixin [1 ]
Lin, Fuyong
机构：
[1] Huaqiao Univ, Coll Informat Sci & Engn, Quanzhou, Peoples R China
来源：
2012 INTERNATIONAL CONFERENCE ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING (ICMPBE2012) | 2012年 / 33卷
关键词：
image denoising; multiresolution theory; orthogonal B-spline;
D O I：
10.1016/j.phpro.2012.05.137
中图分类号：
Q6 [生物物理学];
学科分类号：
071011 ;
摘要：
We apply new multiresolution theory based on orthogonal spline to image denoising. Just like spline interpolation, the new theory can well approximate any function. It also integrates symmetry, therefore there is no loss or getting and no phase derivation when one reconstruct signal after decomposition. The new method is applied to image denoising via soft-thresholding. Comparing with commonly used wavelets, the new method can well separate noise and image and shows potential application in improving vision quality and preserving edge information for denoised image. (C) 2012 Published by Elsevier B.V. Selection and/or peer review under responsibility of ICMPBE International Committee.
引用
收藏
页码：798 / 803
页数：6
相关论文
共 50 条
  • [31] Image Denoising using Contourlet Transform
    Sivakumar, R.
    Balaji, G.
    Ravikiran, R. S. J.
    Karikalan, R.
    Janaki, S. Saraswathi
    SECOND INTERNATIONAL CONFERENCE ON COMPUTER AND ELECTRICAL ENGINEERING, VOL 1, PROCEEDINGS, 2009, : 22 - 25
  • [32] An Image Denoising Application Using Shearlets
    Sevindir, Hulya Kodal
    Yazici, Cuneyt
    11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2013, PTS 1 AND 2 (ICNAAM 2013), 2013, 1558 : 2478 - 2481
  • [33] Image denoising using a combined criterion
    Semenishchev, Evgeny
    Marchuk, Vladimir
    Shrafel, Igor
    Dubovskov, Vadim
    Onoyko, Tatyana
    Maslennikov, Stansilav
    MOBILE MULTIMEDIA/IMAGE PROCESSING, SECURITY, AND APPLICATIONS 2016, 2016, 9869
  • [34] Image denoising using a tight frame
    Shen, LX
    Papadakis, M
    Kakadiaris, IA
    Konstantinidis, I
    Kouri, D
    Hoffman, D
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2006, 15 (05) : 1254 - 1263
  • [35] Image denoising using cloud images
    HuanjingYue
    Sun, Xiaoyan
    JingyuYang
    FengWu
    APPLICATIONS OF DIGITAL IMAGE PROCESSING XXXVI, 2013, 8856
  • [36] Image Denoising Using Weighted Averaging
    Zhou Dengwen
    Shen Xiaoliu
    2009 WRI INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND MOBILE COMPUTING: CMC 2009, VOL I, 2009, : 400 - 403
  • [37] Image Denoising using Ridgelet Shrinkage
    Kumar, Pawan
    Bhurchandi, K. M.
    SIXTH INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2014), 2015, 9443
  • [38] Image denoising using a tight frame
    Shen, L
    Papadakis, M
    Kakadiaris, IA
    Konstantinidis, I
    Kouri, D
    Hoffman, D
    2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING, 2005, : 641 - 644
  • [39] Local Image Denoising Using RAISR
    Zin, Theingi
    Seta, Shogo
    Nakahara, Yusuke
    Yamaguchi, Takuro
    Ikehara, Masaaki
    IEEE ACCESS, 2022, 10 : 22420 - 22428
  • [40] Image Denoising Using Sparse Representations
    Valiollahzadeh, SeyyedMajid
    Firouzi, Hamed
    Babaie-Zadeh, Massoud
    Jutten, Christian
    INDEPENDENT COMPONENT ANALYSIS AND SIGNAL SEPARATION, PROCEEDINGS, 2009, 5441 : 557 - +
12345