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medpy.filter.image.ssd

medpy.filter.image.ssd(minuend, subtrahend, normalized=True, signed=False, size=None, footprint=None, mode='reflect', cval=0.0, origin=0)[source]

Computes the sum of squared difference (SSD) between patches of minuend and subtrahend.

Parameters:

minuend : array_like

Input array from which to subtract the subtrahend.

subtrahend : array_like

Input array to subtract from the minuend.

normalized : bool, optional

Whether the SSD of each patch should be divided through the filter size for normalization. Default is ‘True’.

signed : bool, optional

Whether the accumulative sign of each patch should be returned as well. If ‘True’, the second return value is a numpy.sign array, otherwise the scalar ‘1’. Default is ‘False’.

size : scalar or tuple, optional

See footprint, below

footprint : array, optional

The patch over which to compute the SSD. Either size or footprint must be defined. size gives the shape that is taken from the input array, at every element position, to define the input to the filter function. footprint is a boolean array that specifies (implicitly) a shape, but also which of the elements within this shape will get passed to the filter function. Thus size=(n,m) is equivalent to footprint=np.ones((n,m)). We adjust size to the number of dimensions of the input array, so that, if the input array is shape (10,10,10), and size is 2, then the actual size used is (2,2,2).

mode : {‘reflect’, ‘constant’, ‘nearest’, ‘mirror’, ‘wrap’}, optional

The mode parameter determines how the array borders are handled, where cval is the value when mode is equal to ‘constant’. Default is ‘reflect’

cval : scalar, optional

Value to fill past edges of input if mode is ‘constant’. Default is 0.0

Returns:

ssd : ndarray

The patchwise sum of squared differences between minuend and subtrahend.