tf.image.per_image_whitening()

tf.image.per_image_whitening(image)

Linearly scales image to have zero mean and unit norm.

This op computes (x - mean) / adjusted_stddev, where mean is the average of all values in image, and adjusted_stddev = max(stddev, 1.0/sqrt(image.NumElements())).

stddev is the standard deviation of all values in image. It is capped away from zero to protect against division by 0 when handling uniform images.

Note that this implementation is limited: * It only whitens based on the statistics of an individual image. * It does not take into account the covariance structure.

Args:

• image: 3-D tensor of shape [height, width, channels].

Returns:

The whitened image with same shape as image.

Raises:

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