A study on computationally fast colour image enhancement based on fuzzification of saturation and intensity components. (1st January 2012)

• Record Type: Journal Article
• Authors: Bhadouria, Vivek Singh; Ghoshal, Dibyendu
• Is Part Of: International journal of innovative computing and applications. Volume 4:Number 2(2012)
• Page Start: 67
• Page End: 74
• Publication Date: 2012-01-01
• Subjects: image enhancement -- colour model -- fuzzy logic -- peak signal to noise ratio -- PSNR -- isopreference curve; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

A study on colour image enhancement based on fuzzification of saturation and intensity components has been carried out where the hue (colour content) of the colour image was treated unperturbed. The original images in RGB space were converted into HSI space to segregate the chrominance information from the intensity of the image pixels. Fuzzification and a follow up intensification have been carried out on the saturation and intensity of the colour image signal by using standard formulae. The proposed scheme was tried over three images viz. mandrill, F-16 aeroplane and house. Isopreference curves based on subjective observations for these images have also been studied. The results have indicated a better image enhancement in terms of colour sharpness at the boundaries and detail visibility. The study has further shown that the proposed method is capable of yielding better processing speed using MATLAB and better peak signal to noise ratio (PSNR) compared with the earlier works based on histogram equalisation.