Contrast Enhancement Using Bi-Histogram Equalization With Brightness Preservation

  IJCOT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© - May Issue 2013 by IJCTT Journal
Volume-4 Issue-5                           
Year of Publication : 2013
Authors :Gowthami Rajagopal, K.Santhi

MLA

Gowthami Rajagopal, K.Santhi"Contrast Enhancement Using Bi-Histogram Equalization With Brightness Preservation"International Journal of Computer Trends and Technology (IJCTT),V4(5):1010-1014 May Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract: -Contrast enhancement is an important factor in the image preprocessing step. One of the widely accepted contrast enhancement method is the histogram equalization. Although histogram equalization achieves comparatively better performance on almost all types of image, global histogram equalization sometimes produces excessive visual deterioration. A new extension of bi-histogram equalization called Bi-Histogram Equalization with Neighborhood Metric (BHENM). First, large histogram bins that cause washout artifacts are divided into sub-bins using neighborhood metrics, the same intensities of the original image are arranged by neighboring information. Then the histogram of the original image is separated into two sub-histogram based on the mean of the histogram of the original image; the sub-histogram are equalized independently using refined histogram equalization, which produces flatter histogram. BHENM simultaneously preserved the brightness and enhanced the local contrast of the original image. Simulation result shows better brightness preservation.

 

References-
[1] R. C. Gonzalez, and R. E., Woods, Digital Image Processing, 2nd ed., Prentice Hall, 2002.
[2] Y.-T. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Trans. Consum.Electron., vol. 43, no. 1, pp. 1–8, Feb. 1997.
[3] Y.Wang, Q. Chen, and B. Zhang, “Image enhancement based on equal area dualistic sub-image histogram equalization method,” IEEE Trans.Consum. Electron., vol. 45, no. 1, pp. 68–75, Feb. 1999.
[4] H.Ibrahim and N.S.P Kong ,“ Brightness Preserving Dyanmic Histogram Equalization For Image Contrast Enhancement,” IEEE Trans. Consum. Electron., vol. 53, no. 1, pp. 1752–1758, Nov. 2007.
[5] Chen and A. Ramli , “Minimum mean brightness error bi- histogram equalization in contrast enhancement,” IEEE Trans. Consum.Electron., pp. 1310–1319Nov.2003.
[6] K. S. Sim, C. P. Tso, and Y. Y. Tan, “Recursive sub-image histogram equalization applied to gray scale images,” Pattern Recognition Letters, vol. 28, no. 10, pp. 1209-1221,Nov. 2007.
[7]NyamlkhagvaSengee, and Heung-Kook Choi, “Brightness Preserving Weight Clustering Histogram Equalization,” IEEE Trans. Consumer Electron., vol.54, No.3, August 2008.

Keywords — Bi-Histogram Equalization, Contrast enhancement, Flat Histogram ,Brightness Preservation.