Hybrid Algorithm for Gray-Level Image Contrast Enhancement
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
Nowadays, images play important role in real world but sometimes when they are captured often due to bad weather, atmospheric conditions like fog or due to lower illumination or lightening etc. images are not clear. Image enhancement is a vast area of image processing with its application in different fields. Using this we improve the visual appearance of an image or modify attributes of an image to make it more suitable for a specific application. Improving Quality of those images is always a difficult, challenging, as well as an important task in image processing. This paper presents a novel hybrid method which uses combination of Differential Evolution i.e. DE and particle Swarm Optimization i.e. PSO for contrast enhancement. Experimental results show that the resulting images by the proposed method have good and natural contrasts compared with the resulting images by conventional methods. This comparison will be done on the basis of subjective and objective parameters. Subjective parameter isvisual quality and objective parameters are Fitness function, Entropy value, Intensity/Average value, Detailed variance, Background Variance.
Authors and Affiliations
Dr. Sandeep Kumar, Navdeep Kaur
Keywords
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