I have two series, series1 and series2. My aim is to find how much Series2 is different from Series1,on a bin to bin basis, (each bin represents a particular feature,) automatically/quantitatively.
This image can be seen in its original size by clicking here.
Series1 is the expected result. Series2 is the test/incoming series.
I am providing a histogram plot, where Series2 is represented in dark brown colour. You can also note in the x-axis between 221 and 353 there is a significant variation. ie Series2 is less than Series1. I am coding using C++.
I think, crosscorrelation will help, but produces a value based on similarity rather than dissimilarity. I see people talk about Kolmogorov-Smirnov Test. Is this the test which i should be performing?
UPDATE 1: I am trying to perform a template matching. I have divided my template image in to 8x8 blocks as well as my incoming test image. I am trying to compare one block in template image with the same block(based on the spatial pixel positions) in the test image. I calculate the intensity sum within each block.I obtain series1 for the Template image and have Series2 for the test image.