Testing an image processing algorithm on noisy data
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I wrote an image processing program that train some classifier to recognize some object in the image. now I want to test the response of my algorithm to noise. I wish the algorithm have some robustness to noise.
My question is that, should I train the classifier using noisy version of train dataset, or train the classifier using original version of dataset, and see its performance on noisy data.
Thank you.
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