The local histogram is computed using a sliding window similar to the method described in .
The pixel neighborhood is defined by:
the given structuring element
an interval [g-s0, g+s1] in greylevel around g the processed pixel greylevel
The kernel is flat (i.e. each pixel belonging to the neighborhood contributes equally).
Result image is 8-/16-bit or double with respect to the input image and the rank filter operation.
Approximate bilateral rank filter for local (custom kernel) mean.
Approximate bilateral rank filter for local (custom kernel) mean.
The local histogram is computed using a sliding window similar to the method described in .
The pixel neighborhood is defined by:
the given structuring element
an interval [g-s0, g+s1] in greylevel around g the processed pixel greylevel
The kernel is flat (i.e. each pixel belonging to the neighborhood contributes equally).
Result image is 8-/16-bit or double with respect to the input image and the rank filter operation.
<Unimplemented 'footnote' '.. [1] Huang, T. ,Yang, G. ; Tang, G.. "A fast two-dimensional\n median filtering algorithm", IEEE Transactions on Acoustics, Speech and\n Signal Processing, Feb 1979. Volume: 27 , Issue: 1, Page(s): 13 - 18.'>
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