Paper Info
Title
Fuzzy-Based Histogram Partitioning for Bi-Histogram Equalisation of Low Contrast Images
Abstract
The conventional histogram equalisation (CHE), though being simple and widely used technique for contrast enhancement, but fails to preserve the mean brightness and natural appearance of images. Most of the improved histogram equalisation (HE) methods give better performance in terms of one or two metrics and sacrifice their performance in terms of other metrics. In this paper, a novel fuzzy based bi-HE method is proposed which equalises low contrast images optimally in terms of all considered metrics. The novelty of the proposed method lies in selection of fuzzy threshold value using level-snip technique which is then used to partition the histogram into segments. The segmented sub-histograms, like other bi-HE methods, are equalised independently and are combined together. Simulation results show that for wide-range of test images, the proposed method improves the contrast while preserving other characteristics and provides good trade-off among all the considered performance metrics.
Year
DOI
Venue
2020
10.1109/ACCESS.2020.2965174
IEEE ACCESS
Keywords
DocType
Volume
Contrast enhancement,histogram equalisation,image transformation,fuzzy membership function,dynamic range,optimal threshold
Journal
8
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Mohammad Farhan Khan191.15
Deepali Goyal200.34
Muaffaq M. Nofal300.68
E. Khan45612.71
Rami Al-hmouz532319.34
Enrique Herrera-Viedma613105642.24