Open AccessPlateau limit‐based tri‐histogram equalisation for image enhancement
Author(s) -
Paul Abhisek,
Bhattacharya Paritosh,
Maity Santi P.,
Bhattacharyya Bidyut Kr.
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.1088
Subject(s) - histogram , plateau (mathematics) , image histogram , histogram matching , limit (mathematics) , mathematics , balanced histogram thresholding , adaptive histogram equalization , artificial intelligence , histogram equalization , pattern recognition (psychology) , image (mathematics) , computer science , image processing , image texture , mathematical analysis
An adaptive plateau limit‐based histogram equalisation algorithm is suggested to enhance digital images. Histogram of the image is clipped with a plateau limit to avoid over enhancement. The plateau limit is derived from the average of the mean and the median intensity values to offer the improved enhancement. Clipped histogram is subdivided into three parts, using histogram subdivision limit parameters that are calculated on the basis of the standard deviation of the image. Histogram of individual sub‐image is equalised independently and then combined into a single enhanced image. Experimental results demonstrate that the proposed plateau limit‐based tri‐histogram equalisation algorithm enhances the image quality. Compared with the other traditional plateau and non‐plateau limit‐based histogram equalisation algorithms, quantitative and visual quality assessments effectively validate the superiority of the proposed algorithm.