![]() |
||
Welcome to International Journal of Research in Social Sciences & HumanitiesE-ISSN : 2249 - 4642 | P-ISSN: 2454 - 4671 IMPACT FACTOR: 8.561 |
Abstract
CONTRAST ENHANCEMENT OF SPORTS IMAGES
DR. G. NALLAVAN
Volume: 5 Issue: 2 2015
Abstract:
In this paper two comparative approaches for the contrast enhancement of dark sports images. The contrast of any image is a very important characteristic which decides the quality of image. Low contrast images occur often due to poor or non uniform lighting conditions and sometimes due to the non linearity or small dynamic range of the imaging system. Enhancing the contrast of sports images is of importance since it is difficult to analyse the performance of the team or player with a poor quality image. Though several methods are proposed for gray scale images, enhancing the contrast of colour images is a complicated process. In this paper we have proposed two comparative approaches for the contrast enhancement of colour images and have compared their performance against the standard histogram equalization method. First method is contrast enhancement of colour images using fuzzy rule based method and the second method is using modified sigmoid function. Colour images cannot be processed directly hence a suitable color model is chosen for processing and the proposed methods are implemented. For both the approaches the color images are split into RGB planes and the proposed operation is performed on each plane and finally the planes are concatenated to obtain the enhanced image. Performance of the proposed methods is measured using a factor known as Measure of Contrast and the comparison is represented graphically. Experimental results prove that of the two methods proposed, contrast enhancement using modified sigmoid function provides the highest measure of contrast and can be effectively used for further analysis of sports colour images.
References
- Xinguo Yu, Dirk Farin, “Current and Emerging Topics in Sports Video Processing”, 2005, IEEE,
- Oakley, J. P., and Satherley, B. L. 1 “Improving image quality in poor visibility conditions using a physical model for contrast degradation” IEEE Transactions on Image Processing 7, 1998 , PP.167–179, Giuseppe Bocignone, Antonio Picariello, “Multiscale Contrast Enhancement of Medical Images”, IEEE, 1997, pp 2789-2792.
- Korpi-Anttila, “Automatic color enhancement and scene change detection of digital video”, 2003, Licentiate thesis, Helsinki University of Technology, Laboratory of Media Technology.
- Pfizer S.M. et al, “Adaptive Histogram Equalization and its Variations”, 1998, Computer Vision, Graphics and Image Processing, vol. 39, pp. 355-368.
- F.P.P. De Vries “Automatic, adaptive, brightness independent contrast enhancement', Signal Processing, 1990, vol. 21, pp. 169-182.
- J.A. Stark and W.J. Fitzgerald, 'An Alternative Algorithm for Adaptive Histogram Equalization'. Graphical Models and Image Processing, 1996, vol.56, pp.180-185.
- Lucchese and S.K. Mitra, 'Filtering color images in the xyY color space,' International Journal of Computer Science and Network Security, 2006, Vol.6 No.2A.
- Ding Xiao, Jun Ohya, “Contrast enhancement of color images based on wavelet transform and human visual system”,Proc of the IASTED International Conference Graphics & Visualisation in Engineering, 2007, January 3-5.
- Srinivasan, S, “Adaptive Histogram-Based Video Contrast Enhancement,” 2005, Patent Filing.
- N.R.Mokhtar et al, “Image Enhancement Techniques Using Local,Global, Bright, Dark and Partial Contrast Stretching For Acute Leukemia Images”, Proceedings of the World Congress on Engineering, 2009, Vol I WCE
- S. Srinivasan and N. Balram, “Adaptive Contrast Enhancement Using Local Region Stretching, Proc.of ASID’06, 8-12 Oct, 2006, New Delhi, pp 152-155.
- Gustav J.Braun & Mark D.Fairchild, “Image lightness rescaling using Sigmoidal Contrast Enhancement Functions” 1999.
- Naglaa Yehya Hassan1, and Norio Aakamatsu, (2006) “Contrast Enhancement Technique of Dark Blurred Image”, IJCSNS, International Journal of Computer Science and Network Security, VOL.6 No.2A, pp 223-226.
- Atul Bansal et al, “Simulation of Image Enhancement Techniques using Matlab”, Proceedings of the First Asia International Conference on Modelling & Simulation, (AMS’07), 2007, IEEE.
- Y. T. Kim “Contrast Enhancement Using Brightness Preserving Bi-Histogram Equalization”,IEEE Trans., Consumer Electronics. 1997, vol. 43, no. 1, pp. 1-8.
- S. D. Chen and A. R. Ramli “Minimum Mean Brightness Error Bi-Histogram Equalization in Contrast Enhancement” , 2003, IEEE Trans., Consumer Electronics, vol. 49, no. 4, pp. 1310-131.
- M. Abdullah-Al-Wadud, et al , “A Dynamic Histogram Equalization for Image Contrast Enhancement”, IEEE Trans., Consumer Electronics , 2007, vol.53, no. 2, pp. 593–600.
- H. Ibrahim, and N. S. P. Kong. “Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement”, 2007, IEEE Trans.,Consumer Electronics ,vol. 53, no.4, pp. 1752–1758.
- P.Kannan. S.Deepa and R.Ramakrishnan, “Contrast Enhancement of Sports Images using modified sigmoid function”, 2010, Proceedings of IEEE International Conference on Communication Control and Communication Technologies.
- Rafael C.Gonzalez et al, “Digital Image Processing, 2008, 2 nd Ed, PHI.
- Zadeh, L. A. “Fuzzy Sets”, Information and Control 8, 1965, pp. 338-353.

Refer & Earn |