1) Bivariate Shrinkage
双变量收缩
1.
Locally adaptive image denoising based on bivariate shrinkage function;
基于双变量收缩函数的局域自适应图像去噪
2.
The corresponding nonlinear threshold functions (bivariate shrinkage function) are derived from the model using the Bayesian estimation theory.
基于贝叶斯估计理论,得到了相应的非线性阈值函数(双变量收缩函数)。
3.
Firstly, a bivariate probability distribution model was introduced to model the statistical behaviors of wavelet coefficients, and then the corresponding nonlinear threshold function (bivariate shrinkage function) was de.
基于贝叶斯估计理论,得到了相应的双变量收缩函数;基于层内局域方差估计,得到了一种局域自适应去噪算法。
2) bivariate shrinkage function
双变量收缩函数
1.
Combining bivariate shrinkage function with enhancement of wavelet significant coefficients,a novel method is proposed for removing noise from images with speckle,which allows us to consider the particularity of the model for speckle noise.
在充分考虑斑点噪声模型特殊性的基础上,将双变量收缩函数与小波系数显著性增强相结合,提出一种新的用于SAR图像的斑点抑制算法。
3) bi-shrinkage yarn
双收缩变形纱
4) bivariate shrink threshold
双变量萎缩阈值
1.
Complex wavelet transform and bivariate shrink threshold based image denoising;
基于双树复数小波变换和双变量萎缩阈值图像降噪
5) shrinkage
[英]['ʃrɪŋkɪdʒ] [美]['ʃrɪŋkɪdʒ]
收缩收缩量
6) 'Duplex contraction
双重收缩
补充资料：变量与变量值
可变的数量标志和所有的统计指标称作变量。变量的数值表现称作
变量值，即标志值或指标值。变量与变量值不能误用。
变量值，即标志值或指标值。变量与变量值不能误用。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条