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A Comparative Study of Histogram Equalization Techniques and Adaptive Gamma Correction for Color Image Contrast Enhancement

by Chhaya Gautam, Neeraj Tiwari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 15
Year of Publication: 2014
Authors: Chhaya Gautam, Neeraj Tiwari
10.5120/18147-9385

Chhaya Gautam, Neeraj Tiwari . A Comparative Study of Histogram Equalization Techniques and Adaptive Gamma Correction for Color Image Contrast Enhancement. International Journal of Computer Applications. 103, 15 ( October 2014), 1-4. DOI=10.5120/18147-9385

@article{ 10.5120/18147-9385,
author = { Chhaya Gautam, Neeraj Tiwari },
title = { A Comparative Study of Histogram Equalization Techniques and Adaptive Gamma Correction for Color Image Contrast Enhancement },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 15 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number15/18147-9385/ },
doi = { 10.5120/18147-9385 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:36.357529+05:30
%A Chhaya Gautam
%A Neeraj Tiwari
%T A Comparative Study of Histogram Equalization Techniques and Adaptive Gamma Correction for Color Image Contrast Enhancement
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 15
%P 1-4
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The most noteworthy conclusion of image processing is a contrast enhancement. The most regular system for histogram equalization is utilized for retouching contrast within digital images. Histogram equalization is so advantageous and useful for image contrast enhancement method. Nonetheless, the traditional histogram equalization methods normally conclusion in surpassing complexity upgrades which variable the non-common look and noticeable curio of the handled picture. In this paper exhibits an alternate new manifestation of histogram for picture contrast enhancement. A few systems are this station is the measuring used to grant the data histogram. Global Histogram Equalization GHE utilizes the force dissemination of the whole image. Shine safeguarding Bi -Histogram Equalization BBHE utilizes the mean force is adjusted image autonomously. Double Sub -Image Histogram Equalization DSIHE utilizes the average force is adjusted image autonomously. Least Mean Brightness Error Bi -HE MMBEBHE utilizes the partition of image based on edge level, prepares the most modest Absolute Mean Brightness Error AMBE. Recursive Mean -Separate Histogram Equalization RMSHE is more different advance system for histogram adjustment. Extent Limited Bi-Histogram Equalization RLBHE jelly the initially brilliance well in order to separate the threshold that minimizes the intra – class difference. Review same that everybody these methodologies are more straightforward and valuable for image contrast

References
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  7. Otsu, N. 1979 A threshold selection method from gray-level histograms. IEEE Trans Syst. Man Cybern. 9. pp. 62–66.
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  9. Huang, S. C. , Cheng, F. C. and Chiu, Y. S. 2013 Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution IEEE Transactions on Image Processing. Vol. 22. No. 3. pp. 1032-1042.
  10. Shannon, C. 1948 A mathematical theory of communication. Bell Syst. Tech. J. Vol. 27. pp. 379-423.
Index Terms

Computer Science
Information Sciences

Keywords

Color Image Contrast Enhancement Histogram Equalization Brightness Preserving Enhancement Range Limit Histogram Partition.

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