Open Access2D histogram equalisation based on the human visual system
Author(s) -
Kim S.W.,
Choi B.D.,
Park W.J.,
Ko S.J.
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2015.3956
Subject(s) - pixel , human visual system model , artificial intelligence , histogram , contrast (vision) , brightness , computer vision , computer science , weighting , mathematics , pattern recognition (psychology) , image (mathematics) , physics , optics , acoustics
Histogram equalisation (HE) methods using the 2D histogram (2DH) have achieved a great success in contrast enhancement. The 2DH is constructed by using the occurrence of a local pixel pair (LPP) consisting of each pixel and its surrounding pixels. However, the 2DH‐based methods often produce over‐stretching artefacts because the low‐textured regions primarily existing in the image induce a spike at some LPPs in the 2DH. To solve this problem, the 2DH is constructed by employing two properties of the human visual system (HVS) as follows: the HVS has the better brightness discrimination in the dark region according to Weber's law, and the HVS is less sensitive to visual artefacts in the higher‐textured regions. To create a spike‐free 2DH, a weighting function reflecting these two properties of the HVS is designed for the LPP. As compared with the popular 2DH‐based methods, the HE with the proposed 2DH can effectively enhance the image contrast while achieving the best perceptual similarity score between the input and output images.