Adaptive histogram equalization where you can divide the
image into several rectangular domains, compute an
equalizing histogram and modify levels so that they match
across boundaries. Depending on the nature of the nonuniformity
of the image.
Adaptive histogram equalization uses the histogram
equalization mapping function supported over a certain
size of a local window to determine each enhanced density
value. It acts as a local operation. Therefore regionsoccupying different gray scale ranges can be enhanced
simultaneously.
The image may still lack in contrast locally. We therefore
need to apply histogram modification to each pixel based
on the histogram of pixels that are neighbors to a given
pixel. This will probably result in maximum contrast
enhancement. According to this method, we partition the
given image into blocks of suitable size and equalize the
histogram of each sub block. In order to eliminate artificial
boundaries created by the process, the intensities are
interpolated across the block regions using bicubic
interpolating functions.