Image.ssd#

Image.ssd(image2: Any) → float[source]#

Sum of squared differences

Parameters:

image2 (Image) – second image

Raises:

ValueError – image2 shape is not equal to self

Returns:

sum of squared differences

Return type:

scalar

Returns a simple image disimilarity measure which is the sum of the squared differences between the image and image2. The result is a scalar and a value of 0 indicates identical pixel patterns and is increasingly positive as image dissimilarity increases.

Example:

>>> from machinevisiontoolbox import Image
>>> img1 = Image([[10, 11], [12, 13]])
>>> img2 = Image([[10, 11], [10, 13]])
>>> img1.ssd(img2)
np.uint64(4)
>>> img1.ssd(img2+10)
np.uint64(364)
>>> img1.ssd(img2*2)
np.uint64(454)

Note

Not invariant to pixel value scale or offset.

References:
Seealso:

zssd sad ncc