1) complex Gaussian scale mixture
复数高斯尺度混合
1.
An image denoising method using complex Gaussian scale mixtures(CGSMs) model in complex Curvelet transform(CCT) domain is presented.
提出了一种基于复数Curvelet变换域复数高斯尺度混合(CGSM)模型的图像去噪方法。
2) Gaussian scale mixtures(GSM)
高斯尺度混合(GSM)
1.
By combining nonsubsampled contourlet transform with Gaussian scale mixtures(GSM),the marginal distributions of neighbor coefficients in the nonsubsampled contourlet domain are modeled.
提出了一种图像去噪方法,将高斯尺度混合(GSM)模型引入非下采样Contourlet变换(NSCT)域,构造了基于NSCT分解系数的邻域模型,并利用Bayes最小均方(BLS)估计进行局部去噪。
3) Gaussian scale mixture model
高斯混合尺度模型
1.
The traditional wavelet-denoising is based on a selection of the threshold,but a new method based on statistical model in wavelet domain is presented,in which the prior statistical model is Gaussian scale mixture model.
针对传统阈值小波去噪方法未考虑小波域尺度内和尺度间系数相关性的问题,采用基于小波域统计模型的新型去噪方法,图像小波域的先验统计模型采用高斯混合尺度模型。
4) Bayes Least Squares-Gaussian Scale Mixture(sBLS-GSM)
贝叶斯最小平方-高斯尺度混合模型
5) complex Gaussian mixture model
复高斯混合模型
1.
In order to improve the robustness of voice activity detection(VAD),the use of an algorithm based on complex Gaussian mixture model under nonstationary noisy environments was presented.
针对语音激活检测的鲁棒性问题,提出在非平稳噪声环境下使用基于复高斯混合模型的鲁棒语音激活检测算法。
6) Gaussian scale
高斯尺度
1.
In order to find the counterparts of different level a pyramid matching method is taken top-down according to theory of Gaussian scale.
结合传统的角点检测算法,提出一种基于高斯金字塔匹配的尺度不变特征点提取算法PBSI,首先建立高斯金字塔,在每层图像中检测Harris角点,根据高斯尺度理论自上而下找到它们在不同层的对应点,所有层上都有的匹配点就是最终的尺度不变特征点。
补充资料：非密度制约因素(见密度制约因素)
非密度制约因素(见密度制约因素)
l焦非密度制约因素见生态因素、密度制约后
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参考词条