  Enhancement of human vision to get an insight to information content is of
vital importance. The traditional histogram equalization methods have been
suffering from amplified contrast with the addition of artifacts and a
surprising unnatural visibility of the processed images. In order to overcome
these drawbacks, this paper proposes interative, mean, and multi-threshold
selection criterion with plateau limits, which consist of histogram
segmentation, clipping and transformation modules. The histogram partition
consists of multiple thresholding processes that divide the histogram into two
parts, whereas the clipping process nicely enhances the contrast by having a
check on the rate of enhancement that could be tuned. Histogram equalization to
each segmented sub-histogram provides the output image with preserved
brightness and enhanced contrast. Results of the present study showed that the
proposed method efficiently handles the noise amplification. Further, it also
preserves the brightness by retaining natural look of targeted image.
