correlate2d(in1, in2, mode='full', boundary='fill', fillvalue=0)
Cross correlate :None:None:`in1` and in2
with output size determined by :None:None:`mode`, and boundary conditions determined by boundary
and :None:None:`fillvalue`.
When using "same" mode with even-length inputs, the outputs of correlate
and correlate2d
differ: There is a 1-index offset between them.
First input.
Second input. Should have the same number of dimensions as :None:None:`in1`.
A string indicating the size of the output:
full
The output is the full discrete linear cross-correlation of the inputs. (Default)
valid
The output consists only of those elements that do not rely on the zero-padding. In 'valid' mode, either :None:None:`in1` or in2
must be at least as large as the other in every dimension.
same
The output is the same size as :None:None:`in1`, centered with respect to the 'full' output.
A flag indicating how to handle boundaries:
fill
pad input arrays with fillvalue. (default)
wrap
circular boundary conditions.
symm
symmetrical boundary conditions.
Value to fill pad input arrays with. Default is 0.
A 2-dimensional array containing a subset of the discrete linear cross-correlation of :None:None:`in1` with in2
.
Cross-correlate two 2-dimensional arrays.
Use 2D cross-correlation to find the location of a template in a noisy image:
>>> from scipy import signal
... from scipy import misc
... rng = np.random.default_rng()
... face = misc.face(gray=True) - misc.face(gray=True).mean()
... template = np.copy(face[300:365, 670:750]) # right eye
... template -= template.mean()
... face = face + rng.standard_normal(face.shape) * 50 # add noise
... corr = signal.correlate2d(face, template, boundary='symm', mode='same')
... y, x = np.unravel_index(np.argmax(corr), corr.shape) # find the match
>>> import matplotlib.pyplot as pltSee :
... fig, (ax_orig, ax_template, ax_corr) = plt.subplots(3, 1,
... figsize=(6, 15))
... ax_orig.imshow(face, cmap='gray')
... ax_orig.set_title('Original')
... ax_orig.set_axis_off()
... ax_template.imshow(template, cmap='gray')
... ax_template.set_title('Template')
... ax_template.set_axis_off()
... ax_corr.imshow(corr, cmap='gray')
... ax_corr.set_title('Cross-correlation')
... ax_corr.set_axis_off()
... ax_orig.plot(x, y, 'ro')
... fig.show()
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._signaltools.correlate2d
scipy.signal._signaltools.correlate
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