OSA's Digital Library

Journal of Display Technology

Journal of Display Technology

| A JOINT IEEE/OSA PUBLICATION

  • Vol. 9, Iss. 1 — Jan. 1, 2013
  • pp: 44–50

Efficient Histogram Modification Using Bilateral Bezier Curve for the Contrast Enhancement

Fan-Chieh Cheng and Shih-Chia Huang

Journal of Display Technology, Vol. 9, Issue 1, pp. 44-50 (2013)


View Full Text Article

Acrobat PDF (1433 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations
  • Export Citation/Save Click for help

Abstract

Contrast enhancement involves transforming the intensity of pixels from the original state to feature significant impaction on many display devices, including laptops, PDAs, monitors, mobile camera phones, and so on. This paper proposes a new method to enhance the contrast of the input image and video based on Bezier curve. In order to enhance the quality and reduce the processing time, control points of the mapping curve are automatically calculated by Bezier curve which performs in dark and bright regions separately. Using the fast and accurate histogram modification allows the proposed method to transform the intensity well for both image and video. Experimental results demonstrate the effectiveness of the proposed method in providing a promising enhancement outcome with low computational cost.

© 2013 IEEE

Citation
Fan-Chieh Cheng and Shih-Chia Huang, "Efficient Histogram Modification Using Bilateral Bezier Curve for the Contrast Enhancement," J. Display Technol. 9, 44-50 (2013)
http://www.opticsinfobase.org/jdt/abstract.cfm?URI=jdt-9-1-44


Sort:  Year  |  Journal  |  Reset

References

  1. V. J. Schmid, B. Whitcher, A. R. Padhani, G.-Z. Yang, "Quantitative analysis of dynamic contrast-enhanced MR images based on Bayesian P-splines," IEEE Trans. Med. Imag. 28, 789-798 (2009).
  2. D.-H. Kim, E.-Y. Cha, "Intensity surface stretching technique for contrast enhancement of digital photography," Multidimen. Syst. Signal Process. 20, 81-95 (2009).
  3. M. J. Carlotto, "Enhancement of low-contrast curvilinear features in imagery," IEEE Trans. Image Process. 16, 221-228 (2007).
  4. X. Xie, K.-M. Lam, "Face recognition under varying illumination based on a 2D face shape model," Pattern Recogn. 38, 221-230 (2005).
  5. C.-C. Leung, K.-S. Chan, H.-M. Chan, W.-K. Tsui, "A new approach for image enhancement applied to low-contrast-low-illumination IC and document images," Pattern Recogn. Lett. 26, 769-778 (2005).
  6. X. Sun, P. L. Rosin, R. R. Martin, F. C. Langbein, "Bas-relief generation using adaptive histogram equalization," IEEE Trans. Vis. Comput. Graphics 15, 642-653 (2009).
  7. G. Ginesu, D. D. Giusto, V. Margner, "Detection of foreign bodies in food by thermal image processing," IEEE Trans. Ind. Electron. 51, 480-490 (2004).
  8. P.-S. Tsai, C.-K. Liang, T.-H. Huang, H. H. Chen, "Image enhancement for backlight-scaled TFT-LCD displays," IEEE Trans. Circuits Syst. Video Technol. 19, 574-583 (2009).
  9. S. S. Agaian, K. Panetta, A. M. Grigoryan, "Transform-based image enhancement algorithms with performance measure," IEEE Trans. Image Process. 10, 367-382 (2001).
  10. T. Arici, S. Dikbas, Y. Altunbasak, "A histogram modification framework and its application for image contrast enhancement," IEEE Trans. Image Process. 18, 1921-1935 (2009).
  11. R. Schettini, F. Gasparini, S. Corchs, F. Marini, A. Capra, A. Castorina, "Contrast image correction method," J. Electron. Imag. 19, 023005 (2010).
  12. S. Lee, H. Kwon, H. Han, G. Lee, B. Kang, "A space-variant luminance map based color image enhancement," IEEE Trans. Consumer Electron. 56, (2010).
  13. S. Lee, V. H. S. Ha, Y.-H. Kim, "Dynamic range compression and contrast enhancement for digital images in the compressed domain," Opt. Eng. 45, 027008 (2006).
  14. H. D. Cheng, R. Min, M. Zhang, "Automatic wavelet base selection and its application to contrast enhancement," Signal Process. 90, 1279-1289 (2010).
  15. Y.-T. Kim, "Contrast enhancement using brightness preserving bi-histogram equalization," IEEE Trans. Consumer Electron. 43, 1-8 (1997).
  16. S.-D. Chen, A. R. Ramli, "Minimum mean brightness error bi-histogram equalization in contrast enhancement," IEEE Trans. Consumer Electron. 49, 1310-1319 (2003).
  17. Z.-G. Wang, Z.-H. Liang, C.-L. Liu, "A real-time image processor with combining dynamic contrast ratio enhancement and inverse gamma correction for PDP," Displays 30, 133-139 (2009).
  18. F.-C. Cheng, S.-J. Ruan, "Image quality analysis of a novel histogram equalization method for image contrast enhancement," IEICE Trans. Inf. Syst. E93-D, 1773-1779 (2010).
  19. M. Hanmandlu, D. Jha, "An optimal fuzzy system for color image enhancement," IEEE Trans. Image Process. 15, 2956-2966 (2006).
  20. M. Hanmandlu, O. P. Verma, N. K. Kumar, M. Kulkarni, "A novel optimal fuzzy system for color image enhancement using bacterial foraging," IEEE Trans. Instrum. Meas. 58, 2867-2879 (2009).
  21. L. Zhang, L. Zhang, X. Mou, D. Zhang, "FSIM: A feature similarity index for image quality assessment," IEEE Trans. Image Process. 20, 2378-2386 (2011).

Cited By

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited