Wavelet-Based Image Denoising using NeighShrink and BiShrink Threshold Functions

被引:0
|
作者
Kittisuwan, P. [1 ]
Asdornwised, W. [1 ]
机构
[1] Chulalongkorn Univ, Fac Engn, Dept Elect Engn, Digital Signal Proc Res Lab, Bangkok 10300, Thailand
关键词
NeighShrink; MAP estimator; MMSE estimator; Bivariate Shrinkage function;
D O I
10.1109/ECTICON.2008.4600479
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents image-denoising methods performed within wavelet domain scheme by incorporating neighboring coefficients, namely NeighShrink [1], and at the same time, denoising the image with bivariate shrinkage function. The idea of Bivariate Shrinkage function (BiShrink [2]) is to model the signal based on MAP estimation approach. In fact, signal can also be bivariately modeled with MMSE estimator. The first method of this work is to incorporate the BiShrink with MMSE model, called here MMSE_BiShrink. In our second proposed method, we incorporate neighboring wavelet coefficients with BiShrink, which is called here MAP_NBShrink. Finally, we proposed the third approach by applying MMSE estimation method with NeighShrink and BiShrink, which we call here MMSE_NBShrink. Experimental results show that ours proposed methods, MMSE_BiShrink and MAP_NBShrink and MMSE_NBShrink, have better PSNR than NeighShrink and BiShrink, respectively.
引用
收藏
页码:497 / 500
页数:4
相关论文
共 50 条
  • [1] Image Denoising Algorithm Using Regional Threshold by Wavelet-Based Contourlet Transform
    Song Yajun
    Yang Chen
    Yang Jinbao
    [J]. 2016 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS (IIKI), 2016, : 380 - 385
  • [2] Threshold analysis in wavelet-based denoising
    Zhang, L
    Bao, P
    Pan, Q
    [J]. ELECTRONICS LETTERS, 2001, 37 (24) : 1485 - 1486
  • [3] Image denoising using fractal and wavelet-based methods
    Barthel, KU
    Cycon, HL
    Marpe, D
    [J]. WAVELET APPLICATIONS IN INDUSTRIAL PROCESSING, 2003, 5266 : 39 - 47
  • [4] Wavelet-based color image denoising
    Thomas, BA
    Rodríguez, JJ
    [J]. 2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL II, PROCEEDINGS, 2000, : 804 - 807
  • [5] Wavelet-based image denoising using variance field diffusion
    Liu, Zhenyu
    Tian, Jing
    Chen, Li
    Wang, Yongtao
    [J]. OPTICS COMMUNICATIONS, 2012, 285 (07) : 1744 - 1747
  • [6] A wavelet-based image denoising technique using spatial priors
    Pizurica, A
    Philips, W
    Lemahieu, I
    Acheroy, M
    [J]. 2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL III, PROCEEDINGS, 2000, : 296 - 299
  • [7] Wavelet-based image denoising using three scales of dependency
    Chen, G.
    Zhu, W-P.
    Xie, W.
    [J]. IET IMAGE PROCESSING, 2012, 6 (06) : 756 - 760
  • [8] Wavelet-based image denoising using hidden Markov models
    Fan, GL
    Xia, XG
    [J]. 2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL III, PROCEEDINGS, 2000, : 258 - 261
  • [9] Anisotropic Wavelet-Based Image Denoising Using Multiscale Products
    He, Ming
    Wang, Hao
    Xie, Hong-fu
    Yang, Ke-jun
    Gao, Qing-Wei
    [J]. CEIS 2011, 2011, 15
  • [10] Wavelet-based denoising using subband dependent threshold for ECG signals
    Poornachandra, S.
    [J]. DIGITAL SIGNAL PROCESSING, 2008, 18 (01) : 49 - 55