skimage.filters.rank.generic

General Description

These filters compute the local histogram at each pixel, using a sliding window similar to the method described in ^[1]. A histogram is built using a moving window in order to limit redundant computation. The moving window follows a snake-like path:

...------------------------↘ ↙--------------------------↙ ↘--------------------------...

The local histogram is updated at each pixel as the footprint window moves by, i.e. only those pixels entering and leaving the footprint update the local histogram. The histogram size is 8-bit (256 bins) for 8-bit images and 2- to 16-bit for 16-bit images depending on the maximum value of the image.

The filter is applied up to the image border, the neighborhood used is adjusted accordingly. The user may provide a mask image (same size as input image) where non zero values are the part of the image participating in the histogram computation. By default the entire image is filtered.

This implementation outperforms skimage.morphology.dilation for large footprints.

Input images will be cast in unsigned 8-bit integer or unsigned 16-bit integer if necessary. The number of histogram bins is then determined from the maximum value present in the image. Eventually, the output image is cast in the input dtype, or the output_dtype if set.

To do

• add simple examples, adapt documentation on existing examples

• add/check existing doc

• adapting tests for each type of filter

References