equalize_adapthist(image, kernel_size=None, clip_limit=0.01, nbins=256)
An algorithm for local contrast enhancement, that uses histograms computed over different tile regions of the image. Local details can therefore be enhanced even in regions that are darker or lighter than most of the image.
For color images, the following steps are performed:
The image is converted to HSV color space
The CLAHE algorithm is run on the V (Value) channel
The image is converted back to RGB space and returned
For RGBA images, the original alpha channel is removed.
The values returned by this function are slightly shifted upwards because of an internal change in rounding behavior.
Input image.
Defines the shape of contextual regions used in the algorithm. If iterable is passed, it must have the same number of elements as image.ndim
(without color channel). If integer, it is broadcasted to each :None:None:`image` dimension. By default, kernel_size
is 1/8 of image
height by 1/8 of its width.
Clipping limit, normalized between 0 and 1 (higher values give more contrast).
Number of gray bins for histogram ("data range").
Equalized image with float64 dtype.
Contrast Limited Adaptive Histogram Equalization (CLAHE).
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them