Open Access   Article

An improved image enhancement approach with HSI color Fuzzy decision modelling

Mehzabeen Kaur1 , Baljit Singh Khehra2

1 Dept of Computer Science, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib, Punjab, India.
2 Dept of Computer Science, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib, Punjab, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 6-13, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.613

Online published on Jul 31, 2018

Copyright © Mehzabeen Kaur, Baljit Singh Khehra . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Citation

IEEE Style Citation: Mehzabeen Kaur, Baljit Singh Khehra, “An improved image enhancement approach with HSI color Fuzzy decision modelling”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.6-13, 2018.

MLA Style Citation: Mehzabeen Kaur, Baljit Singh Khehra "An improved image enhancement approach with HSI color Fuzzy decision modelling." International Journal of Computer Sciences and Engineering 6.7 (2018): 6-13.

APA Style Citation: Mehzabeen Kaur, Baljit Singh Khehra, (2018). An improved image enhancement approach with HSI color Fuzzy decision modelling. International Journal of Computer Sciences and Engineering, 6(7), 6-13.

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Abstract

The image enhancement is the most prominent topic among researchers to introduce more amendments in this domain. The image enhancement covers a large number of techniques, mechanisms and ways to enhance the image. The contrast enhancement or to improve the brightness of the image is one of the way to improve the quality of the image. This study develops a novel approach for image contrast enhancement by considering HSI color model to extract the Hue, Saturation and Intensity of the image. Then the fuzzy inference system is applied to improve the intensity of the image pixels. The simulation is done by considering a set of four different images. The performance of the proposed work is evaluated in the terms of Detail Variance and Background Variance. The proposed work is compared with the traditional GLE (Global Local Image Enhancement), Enhanced AHE (Adaptive Histogram Equalization) and Original Image. The simulation results delineates that the proposed work performs outstanding in comparison to the tradition GLE, Enhanced AHE and original image.

Key-Words / Index Term

Image Enhancement, Contrast Enhancement, Color Model, HIS Model, Fuzzy Inference Model

References

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