How does matlab perform the image zero-centering in input layer?
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I am using the CNN to classify the objects. In input layer matlab itself implements the training data to zero-center by default.
I am wondering how it is performing this zero centering? Is it the per-pixel mean of channel-wise mean for image data? Is it dividing the images by traing data standard deviation?
inputlayer = imageInputLayer(inputSize,Name,Value)
'Normalization' — Data transformation 'zerocenter' (default) | 'none'
Data transformation to apply every time data is forward-propagated through the input layer,
specified as the comma-separated pair consisting of 'Normalization' and one of the following.
'zerocenter' — The software subtracts its mean from the training set.
'none' — No transformation.
Example: 'Normalization','none'
Data Types: char
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Arnav Mendiratta
2017-6-12
Zerocenter normalization means having the data dimensions of approximately the same scale. This is done by dividing each dimension (channel) by its standard deviation once it has been zero-centered. Zero-centering means subtracting the mean from each of these dimension so that "data cloud" is centered towards the origin.
This answer talks about the motivation behind using this approach for CNN.
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