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An Integrated CEA Approach for Color Light Source Estimation
Author(s) -
Harpreet Kaur,
Sandeep Sharma
Publication year - 2017
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2017.02.07
Subject(s) - computer science , color normalization , histogram equalization , color constancy , artificial intelligence , computer vision , brightness , normalization (sociology) , adaptive histogram equalization , color histogram , histogram , color gel , color image , image processing , image (mathematics) , optics , chemistry , physics , organic chemistry , layer (electronics) , sociology , anthropology , thin film transistor
Color constancy is an element of human vision framework which guarantees that the apparent color of items under fluctuating light conditions generally remains constant. It is fundamentally used to eliminate the color cast in the picture. Color Cat is a quick and precise learning-based methodology for accomplishing computational color constancy. However, despite everything it confronts a few limitations like poor brightness due to normalization used. Furthermore it doesn't promise edge preservation. So to overcome these issues a CEA strategy has been proposed which is a hybrid model based on Color Cat, Edge preservation filter and Adaptive histogram Equalization. As Adaptive histogram Equalization is exceptionally valuable for contrast improvement and edges are protected by edge preservation filter. Experimental results show that the proposed CEA approach outperforms over existing techniques.

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