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