Converts clusters from raw channel intensity to their fraction of the intensity for that cluster
A list of color clusters such as those returned
A list of the same size and structure as the input list, but with the cluster normalized as described.
This is a useful option if your images have a lot of variation in lighting, but obviously comes at the cost of reducing variation (if darker and lighter colors are meaningful sources of variation in the dataset).
For example, a bright yellow (R=1, G=1, B=0) and a darker yellow (R=0.8, G=0.8, B=0) both have 50% red, 50% green, and 0% blue, so their normalized values would be equivalent.
A similar but less harsh alternative would be to use HSV rather than RGB for
pixel binning and color similarity clustering by setting
clustering functions and specifying a low number of 'value' bins (e.g.
bins=c(8, 8, 2)).
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