Paper Info
Title
A novel optimal fuzzy color image enhancement using particle swarm optimization
Abstract
This paper presents a new approach to enhance the contrast of color images. The intensity component of Hue, Saturation and Intensity (HSV) color model is fuzzified using Global intensification operator (GINT). A new objective measure called contrast information factor is introduced which is optimized using particle swarm optimization technique to learn the parameters. The enhanced image is evaluated by its entropy, index of fuzziness, contrast information and visual quality factor. Subjective and objective evaluation results clearly show the improvement in the quality of the underexposed images in addition of preserving color and specific image features. Also the shape of the histogram is preserved. The results are also compared with histogram equalization technique.
Year
DOI
Venue
2013
10.1109/IC3.2013.6612237
Contemporary Computing
Keywords
Field
DocType
entropy,fuzzy set theory,image colour analysis,image enhancement,particle swarm optimisation,GINT,HSV,contrast enhancement,contrast information factor,entropy,fuzziness index,global intensification operator,histogram equalization technique,histogram shape,hue saturation and intensity color model,image features,intensity component,objective measure,optimal fuzzy color image enhancement,particle swarm optimization,visual quality factor,Contrast information factor,enhancement,particle swarm optimization(PSO),underexposed image
Particle swarm optimization,HSL and HSV,Histogram,Computer vision,Pattern recognition,Computer science,Hue,Adaptive histogram equalization,Artificial intelligence,Histogram equalization,Color normalization,Color image
Conference
ISSN
ISBN
Citations 
2572-6110
978-1-4799-0190-6
0
PageRank 
References 
Authors
0.34
11
4
Name
Order
Citations
PageRank
Hanmadlu, M.100.34
Shaveta Arora200.34
Gaurav Gupta301.69
Latika Singh400.34