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Reseach Article

Improving Edge based Color Constancy using Grid based Sampling

by Buta Singh, Ashok Kumar Bathla
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 82 - Number 17
Year of Publication: 2013
Authors: Buta Singh, Ashok Kumar Bathla
10.5120/14256-2445

Buta Singh, Ashok Kumar Bathla . Improving Edge based Color Constancy using Grid based Sampling. International Journal of Computer Applications. 82, 17 ( November 2013), 25-33. DOI=10.5120/14256-2445

@article{ 10.5120/14256-2445,
author = { Buta Singh, Ashok Kumar Bathla },
title = { Improving Edge based Color Constancy using Grid based Sampling },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 82 },
number = { 17 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 25-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume82/number17/14256-2445/ },
doi = { 10.5120/14256-2445 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:58:00.254904+05:30
%A Buta Singh
%A Ashok Kumar Bathla
%T Improving Edge based Color Constancy using Grid based Sampling
%J International Journal of Computer Applications
%@ 0975-8887
%V 82
%N 17
%P 25-33
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Color constancy refers to stable psychological tendency in perception even the lighting circumstances changed and it plays an important role in many computer vision applications. Color constancy is the ability to measure the impact of light onto a digital image independent of the color of the light source. Many color constancy algorithms for estimating the color of the light source, are developed so far but all the existing algorithm are based on single light source i. e. they consider that an image is affected by only one light source or single uniform illumination, which is not the case every time, because an image may be affected with more than one illuminations. The illusion of single light source is now violated by multiple sources of light. In this paper, we will discuss a new method which considers that an image is affected by multiple sources of light, without any clue about the color of the light sources. Grid based sampling technique along with Grey Edge algorithm is used to estimate the color of multiple light sources. The use of Bilateral Filter after applying color correction is giving most promising results and it has provided the consistency of this algorithm over different types of images taken from different datasets. Experimental and visual results show that the proposed method achieves much better results than existing methods for color constancy. The qualitative results are tested over some well known parameters i. e. Median Angular Error (MAE), Peak Signal to Noise Ratio (PSNR) etc.

References
  1. Martin Savc, Damjan Zazula, Bozidar Potocnik, "A Novel Color-Constancy Algorithm: A Mixture of Existing Algorithms" (Journal of the Laser and Health Academy Vol. 2012, No. 1).
  2. Arjan Gijsenij and Theo Gevers "Color Constancy Using Natural Image Statistics and Scene Semantics" (IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 4, April 2011).
  3. Ayan Chakrabarti, Keigo Hirakawa, and Todd Zickler "Color Constancy with Spatio-Spectral Statistics" (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011).
  4. David H. Foster "Color Constancy" (Vision Research, 51, 674-700 (2011)).
  5. Michael Bleier, Christian Riess, Shida Beigpour, Eva Eibenberger, Elli Angelopoulou, Tobias Troger, Andr´e Kaup "Color Constancy and Non-Uniform Illumination: Can Existing Algorithms Work?",(IEEE Workshop on Color and Photometry in Computer Vision 2011).
  6. Arjan Gijsenij, Theo Gevers, Joost van de Weijer "Computational Color Constancy: Survey and Experiments"(IEEE Transactions on Image Processing, Vol. X, No. X, Month 2010).
  7. Arjan Gijsenij • Theo Gevers • Joost van deWeijer "Generalized Gamut Mapping using Image Derivative Structures for Color Constancy" (Springer, Int J Comput . Vis (2010)).
  8. Anustup Choudhury and Ge´rard Medioni "Color Constancy Using Standard Deviation of Color Channels" (IEEE International Conference on Pattern Recognition 2010).
  9. S. Bianco,G. Ciocca,C. Cusano?, R. Schettini "Automatic color constancy algorithm selection and combination" (Elsevier, Pattern Recognition 43 (2010)).
  10. Javier Vazquez, C. Alejandro Párraga, Maria Vanrell and Ramon Baldrich, "Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset" (Society for Imaging Science and Technology May-June 2009).
  11. Marc Ebner "Color Constancy Based on Local Space Average Color" (Machine Vision and Applications Vol. 11, No. 5, pp. 283-301, July, 2009).
  12. Arjan Gijsenij, Theo Gevers, and Marcel P. Lucassen "Perceptual Analysis of Distance Measures for Color Constancy Algorithms" (Optical Society of America, Vol. 26, No. 10/October 2009).
  13. Joost van de Weijer, Cordelia Schmid, Jakob Verbeek, Diane Larlus. "Learning Color Names for Real- World Applications" (IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. XX, NO. Y,(2009)).
  14. Joost van de Weijer, Theo Gevers, and Arjan Gijsenij,"Edge-Based Color Constancy" (IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 16, NO. 9, SEPTEMBER 2007).
  15. Vivek Agarwal, Besma R. Abidi, Andreas Koschan Mongi A. Abidi "An Overview of Color Constancy Algorithms" (Journal of Pattern Recognition Research 1 (2006).
  16. G. Finlayson and Elisabetta Trezzi, "Shades of gray and colour constancy. " (2004).
  17. J. van de Weijer Th. Gevers, "Color Constancy based on the Grey-Edge Hypothesis" (IEEE 2005).
  18. Kobus Barnard, Vlad Cardei, and Brian Funt "A Comparison of Computational Color Constancy Algorithms—Part I: Methodology and Experiments With Synthesized Data" (IEEE Transactions on Image Processing Vol. 11, No. 9, September 2002).
  19. D. A. Forsyth "A Novel Algorithm for Color Constancy" (International Journal of Computer Vision, 1990).
  20. Edwin H. Land, "The Retinex Theory of Color Vision" (December 1977).
  21. Arjan Gijsenij, Rui Lu, and Theo Gevers "Color Constancy for Multiple Light Sources" (IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 21, NO. 2, FEBRUARY 2012).
  22. Anustup Choudhury and Gérard Medioni, "Color Constancy using Denoising Methods and Cepstral Analysis" (University of Southern California).
  23. Deepak Kumar Dewangan and Yogesh Rathore, "Image Quality Costing of Compressed Image Using Full Reference Method", Int. J. Tech. Vol. 1, Issue 2, 2011.
  24. Arjan Gijsenij, Rui Lu, and Theo Gevers, "Color Constancy for Multiple Light Sources", IEEE Transactions on Image Processing", Vol. 21, No. 2, February 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Color Constancy Illumination Computer Vision Median Angular Error (MAE) and Peak Signal to Noise Ratio (PSNR).