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Jan 20, 2014 at 9:43 vote accept Dawid D
Jan 17, 2014 at 15:37 comment added lennon310 @DawidD thank you very much for pointing out! You are right we don't need corr_2 since it is always zero. My code is just a normalized cross correlation (scribblethink.org/Work/nvisionInterface/nip.pdf), and there is no corr_2 either. Thank you:)
Jan 17, 2014 at 15:15 comment added Dawid D @lennon310 Thank you for your answer. We are using ImageJ so whole ours code is in Java. We are implementing division by standard driviation in the sumtable schema because there is a lot of calculations. I only doesn't understand corr_2 line there will by zero always becouse sum of element with subtrac mean value will always zero. Can an you explain please, why are you multiplying mean value of image by sum of template value with subtract mean value?
Jan 13, 2014 at 17:44 history edited lennon310 CC BY-SA 3.0
added 87 characters in body
Jan 13, 2014 at 17:43 comment added lennon310 @Aaron thanks Aaron. Yes I found that zero padding may not a big issue, it is probably mainly due to the scaling problem. I deleted that part in my answer. Thanks
Jan 13, 2014 at 17:20 comment added Aaron I think he does need to do zero padding if he wants to do FFT based convolution. You got away with not having it by using conv2 instead.
Jan 13, 2014 at 5:28 history answered lennon310 CC BY-SA 3.0