Một phương pháp mới nâng cao độ tương phản ảnh màu theo hướng tiếp cận trực tiếp

  • Nguyễn Văn Quyền Trường Đại học Hải Phòng
  • Nguyễn Tân Ân Viện Quản lý giáo dục
  • Trần Thái Sơn
  • Ngô Hoàng Huy
  • Đặng Duy An


Image contrast enhancement techniques have two mainly methods: indirect method and direct method. While indirect methods only modify the histogram without defining any specific contrast measure, the direct methods establish a criterion of contrast measurement and enhance the image by improving the contrast measure. Among many direct methods, only the studies by Cheng and Xu modified the contrast at each point of grayscale image using a contrast measure [6, 7].

In this paper we propose a new method for enhancing the contrast of color images based on the direct method. The experimental results demonstrate that the combination of our proposed method with Fuzzy C_Mean (FCM) clustering algorithms performs well on different color images.

Author Biographies

Nguyễn Văn Quyền, Trường Đại học Hải Phòng
Phòng Quản lý khoa học - Trường Đại học Hải Phòng
Nguyễn Tân Ân, Viện Quản lý giáo dục
Khoa Công nghệ thông tin - Viện Qản lý giáo dục
Trần Thái Sơn
Viện Công nghệ thông tin, Viện Hàn Lâm và khoa học Việt Nam
Ngô Hoàng Huy
Viện Công nghệ thông tin, Viện Hàn Lâm và khoa học Việt Nam
Đặng Duy An
Viện máy và dụng cụ Công nghiệp, Bộ Công Thương.


S. S. Agaian, S. Blair and K. A. Panetta, “Transform coefficient histogram-based image enhancement algorithms using contrast entropy”, IEEE Trans. Image Processing, vol. 16, no. 3, (2007): 741-758.

Arici T., Dikbas S., and Altunbasak Y., “A Histogram Modification Framework and Its Application for Image Contrast Enhancement,” IEEE Transactions on Image Processing, vol. 18, no. 9, (2009):1921-1935.

A. Beghdadi, A.L. Negrate, “Contrast enhancement technique based on local detection of edges”, Comput. Vision Graphics Image Process. 46 (1989):162–174.

Bezdek, James C. Pattern recognition with fuzzy objective function algorithms. Springer Science & Business Media, (2013).

A.O. Boudraa and E. H. S. Diop, “Image contrast enhancement based on 2D teager-kaiser operator”, Proc. of the IEEE International Conference on Image Processing, (2008.): 3180-3183.

Cheng H.D, Huijuan Xu, “A novel fuzzy logic approach to contrast enhancement”, Pattern Recognition 33 (2000):809-819.

Cheng H.D., Mei Xue, Shi X,J., “Contrast enhancement based on a novel homogeneity measurement”, Pattern Recognition 36 (2003):2687 – 2697.

L.Dash, B.N. Chatterji, “Adaptive contrast enhancement and de-enhancement” , Pattern Recognition 24 (1991) :289–302.

A.P. Dhnawan, G. Buelloni, R. Gordon, Enhancement of mammographic features by optimal adaptive neighborhood image processing, IEEE Trans. Med. Imaging 5 (1986):8–15.

M. M. Gupta, J. Qi, “Theory of T-norms and fuzzy inference methods”, Fuzzy Sets and Systems 40, (1991):431-450.

Hanmandlu M., Devendra Jha, Rochak, “Color image enhancement by fuzzy intensification”, Pattern Recognition Letters 24 (2003):81–87.

Hanmandlu M, Devendra Jha, “An Optimal Fuzzy System for Color Image Enhancement”, IEEE Transactiong on Image Processiong, Vol. 15, No.10 (2006): 2956-2966.

S. Lee, “An efficient content-based image enhancement in the compressed domain using Retinex theory”, IEEE Trans. Circuits and Systems for Video Technology, vol. 17, no. 2, pp. (2007):199-213.

Ponomarenko N. Ponomarenko, L. Jin, O. Ieremeiev, V. Lukin, K. Egiazarian, J. Astola, B. Vozel, K. Chehdi, M. Carli, F.Battisti, C.-C. Jay Kuo, “Image database TID2013: Peculiarities, results and perspectives, Signal Processing”, Imag Communication, vol. 30, Jan. (2015):57-77.

M. Shakeri, M.H. Dezfoulian, H. Khotanlou, A.H. Barati, Y. Masoumi, Image contrast enhancement using fuzzy clustering with adaptive cluster parameter and sub-histogram equalization, Digital Signal Processing 62, (2017) :224–237.

Shen-Chuan Tai, Ting-Chou Tsai, Yi-Ying Chang, Wei-Ting Tsai and Kuang-Hui Tang, “Contrast Enhancement through Clustered Histogram Equalization”, Research Journal of Applied Sciences, Engineering and Technology 4(20), (2012):3965-3968, ISSN: 2040-7467.

M. J. Soha and A. A. Schwartz, “Multi-dimensional histogram normalization contrast enhancement,” in Proc. 5th Canad. Symp.. Remote Sensing, (1978):86–93.

Bài báo