Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution
Sandeep 1 , M. Suresha2
Section:Research Paper, Product Type: Journal Paper
Volume-7 ,
Issue-1 , Page no. 185-191, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.185191
Online published on Jan 31, 2019
Copyright © Sandeep, M. Suresha . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Sandeep, M. Suresha, “Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.185-191, 2019.
MLA Style Citation: Sandeep, M. Suresha "Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution." International Journal of Computer Sciences and Engineering 7.1 (2019): 185-191.
APA Style Citation: Sandeep, M. Suresha, (2019). Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution. International Journal of Computer Sciences and Engineering, 7(1), 185-191.
BibTex Style Citation:
@article{Suresha_2019,
author = {Sandeep, M. Suresha},
title = {Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {185-191},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3483},
doi = {https://doi.org/10.26438/ijcse/v7i1.185191}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.185191}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3483
TI - Enhancement of Low-Quality Images using Bi-Histogram Equalization adaptive sigmoid function based on Shifted Gomphertz Distribution
T2 - International Journal of Computer Sciences and Engineering
AU - Sandeep, M. Suresha
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 185-191
IS - 1
VL - 7
SN - 2347-2693
ER -
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Abstract
Image enhancement participate crucial role in image processing area and its main agenda is improves visual quality of an image. Histogram equalization is most prevalent method in contrast enhancement. But its major drawback is over-enhancement, therefore, it generates abnormal appearance. In this paper, proposed a method that solve over brightness problem by separate two histograms based on mean values of V-channel or intensity channel of HSV image. To calculate cumulative density function for each sub-histogram with two sigmoid function with their origins placed on the medians of sub-histogram after Shifted Gomphertz Distribution applied for each sub-histogram and equalized independently using histogram equalization. Experimental results demonstrate that proposed method gives good results compare to other state-of-the-arts methods with respect to over-enhancement.
Key-Words / Index Term
BBHE, Sigmoid function, Shifted Gomphertz Distribution, Under-water images
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