mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 04:23:17 +08:00
Chris Beaumont
71 lines
1.4 KiB
Python
71 lines
1.4 KiB
Python
import numpy as np
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def integral_image(x):
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"""Integral image / summed area table.
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The integral image contains the sum of all elements above and to the
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left of it, i.e.:
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.. math::
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S[m, n] = \sum_{i \leq m} \sum_{j \leq n} X[i, j]
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Parameters
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----------
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x : ndarray
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Input image.
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Returns
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-------
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S : ndarray
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Integral image / summed area table.
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References
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----------
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.. [1] F.C. Crow, "Summed-area tables for texture mapping,"
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ACM SIGGRAPH Computer Graphics, vol. 18, 1984, pp. 207-212.
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"""
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return x.cumsum(1).cumsum(0)
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def integrate(ii, r0, c0, r1, c1):
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"""Use an integral image to integrate over a given window.
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Parameters
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----------
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ii : ndarray
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Integral image.
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r0, c0 : int or ndarray
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Top-left corner(s) of block to be summed.
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r1, c1 : int or ndarray
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Bottom-right corner(s) of block to be summed.
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Returns
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-------
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S : scalar or ndarray
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Integral (sum) over the given window(s).
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"""
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if np.isscalar(r0):
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r0, c0, r1, c1 = [np.asarray([x]) for x in (r0, c0, r1, c1)]
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S = np.zeros(r0.shape, ii.dtype)
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S += ii[r1, c1]
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good = (r0 >= 1) & (c0 >= 1)
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S[good] += ii[r0[good] - 1, c0[good] - 1]
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good = r0 >= 1
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S[good] -= ii[r0[good] - 1, c1[good]]
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good = c0 >= 1
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S[good] -= ii[r1[good], c0[good] - 1]
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if S.size == 1:
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return np.asscalar(S)
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return S
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