학술논문

Contrast Enhancement Using Quantile Separation and Bi-Histogram Equalization
Document Type
Conference
Source
2019 Innovations in Power and Advanced Computing Technologies (i-PACT) Innovations in Power and Advanced Computing Technologies (i-PACT), 2019. 1:1-4 Mar, 2019
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Histograms
Brightness
Probability distribution
Computers
Heuristic algorithms
Technological innovation
Dynamic range
Bi-Histogram Equalization
histogram equalization
maximising
brightness
Language
Abstract
One of the most common methods of contrast enhancement is Histogram Equalization (HE). But it has problems of over-enhancement owing to its global nature and the mean of output brightness does not correlate with the input. Quantile based HE combats both these problems by applying histogram equalization on local sub-histograms. Due to dynamic scaling of the intensity probability distribution, the average brightness of the output correlates with the input image, and at the same time, improves AMBE and MSSI, but falls short in maximising PSNR. As per the current scenario, LQSWDHE has improved upon the short comings of normal Histogram Equalization and has shown better results than competing algorithms. But the algorithm, when simulated for values of Q (number of values), PSNR value appears to decrease, which is undesirable. Therefore the scope of this paper is to propose an improvement to LQSWDHE so as to improve the PSNR value while maintaining the AMBE and MSSI parameters, as they indicate how similar the output is to the input. This has been achieved by the proposed algorithm by introducing a Brightness Preserving Bi-Histogram Equalization block before the original histogram equalization step in the algorithm.