Adaptive Bayes shrinkage threshold 自适应贝叶斯阈值
The DWT decomposes an image into a series of different scalesmaller images,then detail coefficients are enhanced based on threshold shrinkage filter,and obtains the enhanced image after inverse wavelet transform.
图像经过小波分解后可以得到一系列不同尺度上的子带图像,在不同尺度的子带图像上进行基于阈值收缩滤波的细节系数增强,再进行小波重构,即可得到增强后的图像。
参考来源 - 基于小波变换与阀值收缩法的图像增强去噪A method of image enhancement denoising is descibed based on wavelet transform and threshold shrinkage.
提出了一种基于小波变换与阀值收缩法的图像增强去噪方法。
参考来源 - 基于小波变换与阀值收缩法的图像增强去噪·2,447,543篇论文数据，部分数据来源于NoteExpress
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）。
This paper achieves noise reduction by using wavelet packet transform, semisoft shrinkage function, Donoho standard deviation estimate and threshold obtain based on statistics.
计算结果表明：变形统计值与变形监测值吻合较好，统计复相关系数较大，估计标准误差较小。
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