Wavelet Image Restoration and Regularization Parameters Selection

被引:0
|
作者
Qu, Leming [1 ]
机构
[1] Boise State Univ, Dept Math, Boise, ID 83725 USA
来源
FCST 2009: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON FRONTIER OF COMPUTER SCIENCE AND TECHNOLOGY | 2009年
关键词
Wavelet; image restoration; Lasso; AIC; THRESHOLDING ALGORITHM; RECONSTRUCTION; SHRINKAGE; DECONVOLUTION;
D O I
10.1109/FCST.2009.18
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
For the restoration of an image based on its noisy distorted observations, we propose wavelet domain restoration by scale-dependent l(1) penalized regularization method (WaveRSL1). The data adaptive choice of the regularization parameters is based on the Akaike Information Criterion (AIC) and the degrees of freedom (df) is estimated by the number of nonzero elements in the solution. Experiments on some commonly used testing images illustrate that the proposed method possesses good empirical properties.
引用
收藏
页码:241 / 247
页数:7
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