Subtract mean from image

Question

I'm implementing a CNN with Theano. In the paper, I have to do this image preprocess before train the CNN

We extracted RGB patches of 61x61 dimensions associated with each poselet activation, subtracted the mean and used this data to train the convnet model shown in Table 1

Can you tell me what does it mean with "subtracted the mean"? Tell me if these steps are correct (it is what I understood) 1) Compute the mean for Red Channel, Green Channel and Blue Channel for the whole image 2) For each pixel, subtract from red value the mean of red channel, from green value the mean of green channel and the same for the blue channel 3) Is it correct to have negative value or do I have use the abs?

Thanks all!!

Answer 1

You should read paper carefully, but what is the most probable is that they mean mean of the patches, so you have N matrices 61x61 pixels, which is equivalent of a vector of length 61^2 (if there are three channels then 3*61^2). What they do - they simple compute mean of each dimension, so they calculate mean over these N vectors in respect to each of the 3*61^2 dimensions. As the result they obtain a mean vector of length 3*61^2 (or mean matrix/mean patch if you prefer) and they substract it from all of these N patches. Resulting patches will have negatives values, it is perfectly fine, you should not take abs value, neural networks prefer this kind of data.