Testing an image processing algorithm on noisy data

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.