在三维上扩展一维函数进行数据加窗

为了图像（音量）的配准，我想应用一个窗口函数来输入数据，这样非周期性的图像边界不会导致FFT中的条纹。我使用的例子从这里2D数据：在三维上扩展一维函数进行数据加窗

http://mail.scipy.org/pipermail/numpy-discussion/2008-July/036112.html

h = scipy.signal.hamming(n) 
ham2d = sqrt(outer(h,h))

这是可扩展到3D，甚至N-二d？

来源

2014-12-07 msarahan

可能要发布此[Signal Processing]（http://dsp.stackexchange.com/） – wwii 2014-12-07 18:23:59

谢谢，会做。 – msarahan 2014-12-07 18:24:44

@nivag在信号处理指出，每个维度可以独立处理： https://dsp.stackexchange.com/questions/19519/extending-1d-window-functions-to-3d-or-higher

这里是我想出了一个代码（从scikit图像球队修订帮助）：

def _nd_window(data, filter_function): 
    """ 
    Performs an in-place windowing on N-dimensional spatial-domain data. 
    This is done to mitigate boundary effects in the FFT. 

    Parameters 
    ---------- 
    data : ndarray 
      Input data to be windowed, modified in place. 
    filter_function : 1D window generation function 
      Function should accept one argument: the window length. 
      Example: scipy.signal.hamming 
    """ 
    for axis, axis_size in enumerate(data.shape): 
     # set up shape for numpy broadcasting 
     filter_shape = [1, ] * data.ndim 
     filter_shape[axis] = axis_size 
     window = filter_function(axis_size).reshape(filter_shape) 
     # scale the window intensities to maintain image intensity 
     np.power(window, (1.0/data.ndim), output=window) 
     data *= window

来源

2014-12-21 02:55:45 msarahan

在三维上扩展一维函数进行数据加窗

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