Call for Paper - November 2023 Edition
IJCA solicits original research papers for the November 2023 Edition. Last date of manuscript submission is October 20, 2023. Read More

Color Image Enhancement based on Daubechies Wavelet and HIS Analysis

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 47 - Number 13
Year of Publication: 2012
M. Ramakrishnan
Murtaza Saadique Basha

M Ramakrishnan and Murtaza Saadique Basha. Article: Color Image Enhancement based on Daubechies Wavelet and HIS Analysis. International Journal of Computer Applications 47(13):8-11, June 2012. Full text available. BibTeX

	author = {M. Ramakrishnan and Murtaza Saadique Basha},
	title = {Article: Color Image Enhancement based on Daubechies Wavelet and HIS Analysis},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {47},
	number = {13},
	pages = {8-11},
	month = {June},
	note = {Full text available}


Low contrast and poor quality are main problems in the production of images. By using the wavelet transform and HIS color analysis, a new idea is proposed. Color images are usually converted to gray image first in traditional image enhancement algorithms. The detail information was easily lost and at the same time these algorithms enhance noise while they enhance image, which lead to the descent of information entropy. With the combination of the characteristics of multi-scale and multi-resolution of Daubechies wavelet transform and the pre-dominance of histogram equalization, a novel method of color image enhancement based on hue invariability with characteristics of human visual color consciousness in HIS color pattern is presented here. The experimental results showed that this new algorithm can enhance color images effectively and cost less time.


  • Mallat, S. G. : 'Multifrequency channel decompositions of image and wavelet models', IEEE Trans. Acoust. Speech Signal Process. , 1989, 37, (12), pp. 2091–2110
  • Lu, J. , Healy, D. M. , and Weaver, J. B. : 'Contrast enhancement of medical images using multi-scale edge representation', Opt. Eng. , 1994, 33, (7), pp. 2151–2161
  • Yang, G. , and Hansell, D. M. : 'CT image enhancement with wavelet analysis for the detection of small airways disease', IEEE Trans. Med. Imaging, 1997, 16, (6), pp. 953–961
  • Fang, Y. , and Qi, F. : 'A method of wavelet image enhancement based on soft threshold', Comput. Eng. Appl. , 2002, 23, pp. 16–19
  • Zhou, X. , Zhou, S. , Huang, F. , and Zhou, X. T. : 'New algorithm of image enhancement based on wavelet transform', Comput. Appl. , 2005, 25, (3), pp. 606–608.
  • Wu, Y. , and Shi, P. : 'Approach on image contrast enhancement based on wavelet transform', Infrared Laser Eng. , 2003, 32, (1), pp. 4–7.
  • Ruan Qiuqi. Digital Image Processing, Publishing House of Electronics Industry, Beijing 2001.
  • Wang Ping, Cheng Hao, Lou Yingxin. "Color Image Enhancement Based on Hue Invariability". Journal of Image and Graphics. 2007,12(7): 1173-1177.
  • SHI Meihong ,LI Yonggang ,ZHANG Junying. "Novel method of color image enhancement" Journal. Computer Application,2004,24 ?10?,pp. 69-71.
  • Zhang Yanhong, Hou Dewen. "An Image Enhancement Algorithm Based on Wavelet Frequency Division and Bi-histogram Equalization", Journal. Computer Application and Software. 2007. 11, 24(11), pp. 159- 161.
  • L. Lucchese, S. K. Mitra, & J. Mukherjee, A new algorithm based on saturation and desaturation in the xychromaticity diagram for enhancement and re-rendition of color images, Proc. 8th IEEE Conf. on Image Processing, Thessaloniki, Greece, 2001, 1077-1080.
  • M. S. Shyu, & J. J. Leou, A genetic algorithm approach to color image enhancement, International Journal of Pattern Recognition, 31(7), 1998, 871-880
  • 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.
  • Pan, L. Zhang, G. Dai, & H. Zhang, Two denoising methods by wavelet transform, IEEE Trans on Signal Processing, 47(12), 1999, 3401-3406.
  • 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.
  • 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.