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Reseach Article

Color Image Contrast Enhancement using Daubechies D4 Wavelet and Luminance Analysis

by Murtaza Saadique Basha, M. Ramakrishnan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 6
Year of Publication: 2014
Authors: Murtaza Saadique Basha, M. Ramakrishnan
10.5120/14987-9460

Murtaza Saadique Basha, M. Ramakrishnan . Color Image Contrast Enhancement using Daubechies D4 Wavelet and Luminance Analysis. International Journal of Computer Applications. 86, 6 ( January 2014), 6-10. DOI=10.5120/14987-9460

@article{ 10.5120/14987-9460,
author = { Murtaza Saadique Basha, M. Ramakrishnan },
title = { Color Image Contrast Enhancement using Daubechies D4 Wavelet and Luminance Analysis },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 6 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number6/14987-9460/ },
doi = { 10.5120/14987-9460 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:03:28.969330+05:30
%A Murtaza Saadique Basha
%A M. Ramakrishnan
%T Color Image Contrast Enhancement using Daubechies D4 Wavelet and Luminance Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 6
%P 6-10
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a novel approach which address contrast enhancement in color images. The wavelet transform decomposes an image into bands that vary in spatial frequency and orientation. The HSV color model is well suited for color image enhancement methods even though RGB color space is the predominant one. By using Daubechies D4 wavelet transformation and HSV color model, a novel method of color image enhancement based on luminance adjustment is proposed here. The proposed method not only enables approximating digital signals in a better way but also it approximates highly non-linear digital signals. The experimental results showed that this new method can enhance color images effectively.

References
  1. Raman Maini and Himanshu Aggarwal, "A Comprehensive Review of Image Enhancement Techniques" JOURNAL OF COMPUTING, VOLUME 2, ISSUE 3, MARCH 2010
  2. Bhabatosh Chanda and Dwijest Dutta Majumder, 2002, Digital Image Processing and Analysis.
  3. M. Ramakrishnan and Murtaza Saadique Basha "Color Image Enhancement based on Daubechies Wavelet and HIS Analysis" International Journal of Computer Applications Volume 47 - Number 13, 2012
  4. Vasile Buzuloiu, Mihai Ciuc, Rangaraj M. Rangayyan and Constantin Vertan " Adaptive-Neighborhood Histogram Equalization of Color Images" Journal of Electronic Imaging March 2000
  5. M. S. Shyu, & J. J. Leou, A genetic algorithm approach to color image enhancement, International Journal of Pattern Recognition, 31(7), 1998, 871-880.
  6. J. Lu, & D. M. Hearly, Contrast enhancement via multi-scale gradient transformation, Proc. SPIE Conf. on Wavelet Application Orlando, FL,USA,1994, 345-365.
  7. P Sakellaropoulos, L Costaridou and G Panayiotakis "A wavelet-based spatially adaptive method for mammographic contrast enhancement"
  8. B. A. Thomas, R. N. Strickland, & J. J. Rodriguez, Color image enhancement using spatially adaptive saturation feedback, Proc. 4th IEEE Conf. on Image Processing, Santa Barbara, CA, USA, 1997, 30-33.
  9. Sarif Kumar Naik and C. A. Murthy "Hue-Preserving Color Image Enhancement Without Gamut Problem" IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 12, NO. 12, DECEMBER 2003
  10. R. S. Ledley, M. Buas, & T. J. Colab, Fundamentals of true-color image processing, Proc. 10th IEEE Conf. on Pattern Recognition, Los Alamos, CA, USA, 1990.
  11. Y. Xu, J. B. Weaver, D. M. Healy, & J. Lu, Wavelet transform domain filters: A spatially selective noise filtration technique, IEEE Trans. on Image Processing, 3(6), 1994, 747-758.
  12. Y. Kobayashi, & T. Kato, A high fidelity contrast improving model based on human vision mechanism, Proc. IEEE International Conf. on Multimedia Computing and Systems, Florence, Italy, 1999, 578-584.
  13. R. N. Strickland, C. S. Kim, & W. F. McDonnell, Digital color image enhancement based on the saturation component, International Journal of Optical Engineering, 26(7),1987,609-616
Index Terms

Computer Science
Information Sciences

Keywords

Colour Image Enhancement Daubechies Wavelet Transform HIS Analysis Histogram Equalization luminance enhancement HSV color space wavelet transform