The third algorithm proposes a hybrid image denoising algorithm based on wavelet shrinkage and TV diffusion owing to the disadvantage of TV diffusion.
第三种算法根据全变差模型在去除噪声时的缺陷，提出了将非抽样小波和全变差模型结合起来的自适应混合去噪策略。
The principle and process of the second generation transform based on interpolating subdivision is described, and then the selection of wavelet shrinkage is provided.
介绍了基于插值细分法的第二代小波变换的基本原理和变换过程，给出了小波降噪的阈值选取方法。
A fast location algorithm using classifying shrinkage in parameters space and a feature extraction method using improved wavelet cross-zero detection is presented.
提出了参数空间分级收缩的新的定位算法及其改进的小波过零检测的特征提取算法。
And then addressing SAR image speckle denoising, this dissertation proposed a new method based on bivariate shrinkage function combined with enhancement of wavelet significant coefficients.
其次针对SAR图像相干斑抑制问题，提出一种双变量收缩函数与小波系数显著性增强相结合的SAR图像的斑点抑制算法。
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。
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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