Correlation in image processing
In the realm of image processing, correlation stands as a cornerstone, enabling us to extract meaningful insights and make informed decisions from vast visual data sets. correlation operation is similar to convolutional operation or we can say simpler than convolutional. Post is about brief understanding of correlation operation, from theoretical to implementation levels.
What is Correlation in image preprocessing?
Correlation having similar operating steps as convolution operation which also takes an input image and another kernel and traverses the kernel window through the input by computing a weighted combination of pixel neighborhood values with the kernel values and producing the output image.
From above image it seems clear that only difference between correlation and convolution is that convolution flips the kernel twice (with regards to the horizontal and vertical axis) before computing the weighted combination.Whereas correlation maintains the original orientation of the kernel. It’s often used in tasks like template matching, where the orientation of the kernel matters for finding occurrences of the template.