Image Contrast Enhancement based Sub-histogram Equalization Technique without Over-equalization Noise
In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes these regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrasts in the images and the results are compared to the conventional approaches to show its superiority.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084412Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3040
 A. K. Jai, Fundamentals of Digital Image Processing, Prentice-Hall, 1989.
 J. Y. Kim, L. S. Kim, S. H. Hwang, "An Advanced Contrast Enhancement Using Partially Overlapped Sub-Block Histogram Equalization," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 11, No. 4, pp.475-484, 2001.
 C. C. Sun. S. J. Ruan, M. C. Shie, T. W. Pai, "Dynamic Contrast Enhancement based on Histogram Specification," IEEE Transactions on Consumer Electronics, 51(4), pp.1300-1305, 2005.
 J. A. Stark, "Adaptive Image Contrast Enhancement Using Generalizations of Histogram Equalization," IEEE Transactions on Image Processing, 9(5), pp.889-896, 2000.
 Y. T. Kim, "Contrast Enhancement Using Brightness Preserving Bi-Histogram Equalization," IEEE Transactions on Consumer Electronics, 43(1), pp.1-8, 1997.
 Y. Wan, Q. Chen, B.-M. Zhang, "Image enhancement based on equal area dualistic sub-image histogram equalization method", IEEE Trans. Consum. Electron. 45 (1) (1999) 68-75.
 S. D. Chen, A. Rahman Ramli, "Contrast Enhancement using Recursive Mean-Separate Histogram Equalization for Scalable Brightness Preservation," IEEE Transactions on Consumer Electronics, 49(4), pp.1301-1309, 2003.
 Soong-Der Chen, A. Rahman Ramli, "Preserving brightness in histogram equalization based contrast enhancement techniques,"Digital Signal Processing, 12(5), pp.413-428, September 2004.
 Chao Wang and Zhongfu Ye, "Brightness Preserving Histogram Equalization with Maximum Entropy: A Variational Perspective,"IEEE Transactions on Consumer Electronics, 51(4), pp.1326-1334, 2005.
 K. S. Sim, C. P. Tso, and Y. Y. Tan, ""Recursive sub-image histogram equalization applied to gray scale images"", Pattern Recognition Letters, 28(10), pp. 1209-1221, 2007.
 Z. Chen, B. R. Abidi. D. L. Page, M. A. Abidi, "Gray-Level Grouping (GLG): An Automatic Method for Optimized Image Contrast Enhancement-Part I : The Basic Method," IEEE Transactions on Image Processing, 15(8), pp.2290-2302, 2006.
 S. M. Pizer, E. P. Amburn, J. D. Austin, R. Cromartie, A. Geselowitz, T. Greer, B. H. Romeny, J. B. Zimmerman, K. Zuiderveld, "Adaptive Histogram Equalization and Its Variations," Computer Vision Graphics and Image Processing, Vol. 39, pp.355-368, 1987.
 F. Lamberti, B. Montrucchio, A. Sanna, " CMBFHE_a novel contrast enhancement technique based on cascaded multistep binomial filtering histogram equalization," IEEE Transactions on Consumer Electronics, 52(3), pp.966-974, 2006.
 Z. Q. Wu, J. A. Ware, I. D. Wilson, J. Zhang, "Mechanism analysis of highly overlapped interpolation contrast enhancement," IEEE Proceedings Vision, Image & Signal Processing, 153(4), pp.512-520, 2006.