A filtering method based on wavelet transform with local maximum value was discussed. The method could distinguish signal from the noise according to the different features of scale change.
小波变换局部极大值滤波方法利用信号与噪声不同的尺度变化特性来区分信号与噪声，将噪声从信号中分离出来。
Based on the discussion of the theory of wavelet transform of images, a practical multi scale edge detecting method is put forward and the ways to suppress noise interference are discussed.
在对图像的小波变换原理讨论的基础上，提出了一种较为实用的图像多尺度边缘检测方法，同时对如何抑制噪声的干扰进行了讨论。
Based on different properties of the coefficient modulus of the signal in different scale wavelet transform, conjunction the best estimate of gradient algorithm an edge detecting method is proposed.
基于信号在不同尺度下小波变换系数模不同的变化特征，结合最优梯度估计算法提出了一种边缘检测方法。
In this paper, a new method of multi-scale and adaptive thresholds edge detection for image based on wavelet transform was adopted to detect edge of traffic vehicle.
本文把基于小波变换的多尺度自适应阈值图像边缘检测的新方法应用于交通图像边缘检测。
Then, determination method of fractal parameters and scale-invariant interval is given and influence of transform order on the estimation of fractal parameters is also discussed.
其次，给出了分形参数的提取方法和无标度区间，并分析了变换阶数对分形参数估计的影响。
The features extract method of MCSF based on wavelet multi-scale transform is that the image feature of coefficient sub-frequency is decomposed with 3 layer of wavelet multi-scale transform.
基于小波多尺度分解子带主成份的特征提取法，利用小波多尺度分解子带系数图像特征。
The features extract method of MCSF based on wavelet multi-scale transform is that the image feature of coefficient sub-frequency is decomposed with 3 layer of wavelet multi-scale transform.
基于小波多尺度分解子带主成份的特征提取法，利用小波多尺度分解子带系数图像特征。
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