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Linearly scales each image in image to have mean 0 and variance 1.

For each 3-D image x in image, computes (x - mean) / adjusted_stddev, where

  • mean is the average of all values in x
  • adjusted_stddev = max(stddev, 1.0/sqrt(N)) is capped away from 0 to protect against division by 0 when handling uniform images
    • N is the number of elements in x
    • stddev is the standard deviation of all values in x

image An n-D Tensor with at least 3 dimensions, the last 3 of which are the dimensions of each image.

A Tensor with same shape and dtype as image.

ValueError if the shape of 'image' is incompatible with this function.