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The CUDA Handbook: A Comprehensive Guide to GPU Programming by Nicholas Wilt

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Chapter 15. Image Processing: Normalized Correlation

Normalized cross-correlation is a popular template-matching algorithm in image processing and computer vision. The template typically is an image that depicts a sought-after feature; by repeatedly computing a statistic between the template image and corresponding pixels of a subset of an input image, a search algorithm can locate instances of the template that are present in the input image.

The popularity of normalized cross-correlation for this application stems from its amplitude independence, which, in the context of image processing, essentially means that the statistic is robust in the face of lighting changes between the image and the template. Normalized correlation is popular enough, ...

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