spline_filter(Iin, lmbda=5.0)
Filter an input data set, :None:None:`Iin`, using a (cubic) smoothing spline of fall-off lmbda
.
input data set
spline smooghing fall-off value, default is :None:None:`5.0`.
filterd input data
Smoothing spline (cubic) filtering of a rank-2 array.
We can filter an multi dimentional signal (ex: 2D image) using cubic B-spline filter:
>>> from scipy.signal import spline_filter
... import matplotlib.pyplot as plt
... orig_img = np.eye(20) # create an image
... orig_img[10, :] = 1.0
... sp_filter = spline_filter(orig_img, lmbda=0.1)
... f, ax = plt.subplots(1, 2, sharex=True)
... for ind, data in enumerate([[orig_img, "original image"],
... [sp_filter, "spline filter"]]):
... ax[ind].imshow(data[0], cmap='gray_r')
... ax[ind].set_title(data[1])
... plt.tight_layout()
... plt.show()
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._bsplines.spline_filter
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