I was reading a paper related to Auto encoders for my project work. It is required to input images as vectors to the neural network. I couldn't understand a certain sentence due to lack of knowledge of statistics (I guess). I Googled, but the problem is I don't know what it is exactly and searching the same phrase returns the same kind of documents but not their explanation.

We train on 1.6 million 32*32 color images that have been preprocessed by subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images.

What does it mean by "subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images".

I would request you to explain in lay terms since I'm new to all this.

I was reading a paper related to Auto encoders for my project work. It is required to input images as vectors to the neural network. I couldn't understand a certain sentence due to lack of knowledge of statistics (I guess). I Googled, but the problem is I don't know what it is exactly and searching the same phrase returns the same kind of documents but not their explanation.

Source: http://www.cs.toronto.edu/~hinton/absps/esann-deep-final.pdf

We train on 1.6 million 32*32 color images that have been preprocessed by subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images.

What does it mean by "subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images".

My interpretation is: "Subtracting from each pixel its mean value over all images" It means, for a pixel position in an image, subtract the average of values of that pixel position over all images and subtract from the current pixel value.

Am I correct?

It is somewhat ambiguous to me.

Please explain in some math terms.

I was reading a paper related to Auto encoders for my project work. It is required to input images as vectors to the neural network. I couldn't understand a certain sentence due to lack of knowledge of statistics (I guess). I googled, but the problem is I don't know what it is exactly and searching the same phrase returns the same kind of documents but not their explanation.

We train on 1.6 million 32*32 color images that have been preprocessed by subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images.

What does it mean by "subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images".

I would request you to explain in laymen terms since I'm new to all this.

I was reading a paper related to Auto encoders for my project work. It is required to input images as vectors to the neural network. I couldn't understand a certain sentence due to lack of knowledge of statistics (I guess). I Googled, but the problem is I don't know what it is exactly and searching the same phrase returns the same kind of documents but not their explanation.

We train on 1.6 million 32*32 color images that have been preprocessed by subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images.

What does it mean by "subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images".

I would request you to explain in lay terms since I'm new to all this.

I was reading a paper related to Auto encoders for my project work. It is required to input images as vectors to the neural network. I couldn't understand a certain sentence due to lack of knowledge of statistics (I guess). I googled, but the problem is I don't know what it is exactly and searching the same phrase returns the same kind of documents but not their explanation.

We train on 1.6 million 32*32 color images that have been preprocessed by subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images.

What does it mean by "subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images".

I would request you to explain in laymen terms since I'm new to all this.

I was reading a paper related to Auto encoders for my project work. It is required to input images as vectors to the neural network. I couldn't understand a certain sentence due to lack of knowledge of statistics (I guess). I googled, but the problem is I don't know what it is exactly and searching the same phrase returns the same kind of documents but not their explanation.

We train on 1.6 million 32*32 color images that have been preprocessed by subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images.

What does it mean by "subtracting from each pixel its mean value over all images and then dividing by the standard deviation of all pixels over all images".

I would request you to explain in laymen terms since I'm new to all this.