23-2: An Adaptive Contrast Enhancement of Image Using Multi-Scale Histogram Representation

2017 ◽  
Vol 48 (1) ◽  
pp. 318-321 ◽  
Author(s):  
Yu-Feng Jin ◽  
Shen-Sian Syu ◽  
Ming-Jong Jou

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Cesar Bustacara-Medina ◽  
Leonardo Flórez-Valencia




2006 ◽  
Vol 2 (3) ◽  
pp. 229-232 ◽  
Author(s):  
Peng Feng ◽  
Ying-jun Pan ◽  
Biao Wei ◽  
Wei Jin ◽  
De-ling Mi


Author(s):  
Fabian Zöhrer ◽  
Markus T. Harz ◽  
Anke Bödicker ◽  
Heike Seyffarth ◽  
Kathy J. Schilling ◽  
...  


2016 ◽  
Vol 10 (3) ◽  
pp. 206-214 ◽  
Author(s):  
Zetian Mi ◽  
Yijun Zheng ◽  
Huan Zhou ◽  
Minghui Wang


Author(s):  
Sanghyun Byun ◽  
Heunseung Lim ◽  
Soohwan Yu ◽  
Joonki Paik




2018 ◽  
Vol 4 (9) ◽  
pp. 108 ◽  
Author(s):  
Uche Nnolim

This paper describes a proposed fractional filter-based multi-scale underwater and hazy image enhancement algorithm. The proposed system combines a modified global contrast operator with fractional order-based multi-scale filters used to generate several images, which are fused based on entropy and standard deviation. The multi-scale-global enhancement technique enables fully adaptive and controlled color correction and contrast enhancement without over exposure of highlights when processing hazy and underwater images. This in addition to the illumination/reflectance estimation coupled with global and local contrast enhancement. The proposed algorithm is also compared with the most recent available state-of-the-art multi-scale fusion de-hazing algorithm. Experimental comparisons indicate that the proposed approach yields a better edge and contrast enhancement results without a halo effect, without color degradation, and is faster and more adaptive than all other algorithms from the literature.



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