Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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An Improvement of Histogram Equalization Using Edge Information of an Image

영상 에지 정보를 이용한 히스토그램 평활화 기법의 개선

  • Received : 2017.01.13
  • Accepted : 2017.01.23
  • Published : 2017.02.28
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Abstract

The paper presents a histogram equalization method using the edge information of an image to be processed. The basic idea of this method is to carry out histogram equalization with edge information, which is important and essential for object conformation. In the proposed method, the edge information is used to generate histogram for the equalization process. It is found to be effective to suppress the histogram spikes that cause quantum jumps in mapping function for the equalization process. The proposed method is tested for randomly selected 30 images and compared to conventional approaches with a quantitative measure to check it preserves the structural similarity. Experimental results show that the proposed method has better performance and no artifacts caused by histogram spikes.

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References

  1. C.R. Nithyananda, A.C. Ramachandra, and Preethi, "Review on Histogram Equalization based Image Enhancement Techniques," Proceeding of International Conference on Electrical, Electronics, and Optimization Techniques, pp. 2512-2517, 2016.
  2. Y.T. Kim, "Contrast Enhancement Using Brightness Preserving Bi-histogram Equalization," IEEE Transactions on Consumer Electronics, Vol. 43, No. 1, pp. 1-8, 1997. https://doi.org/10.1109/30.580378
  3. Y. Wang, Q. Chen, and B. Zhang, "Image Enhancement Based on Equal Area Dualistic Sub-Image Histogram Equalization Method," IEEE Transactions on Consumer Electronics, Vol. 45, No. 1, pp. 68-75, 1999. https://doi.org/10.1109/30.754419
  4. S.D. Chen and A.R. Ramli, "Contrast Enhancement Using Recursive Mean-separate Histogram Equalization for Scalable Brightness Preservation," IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, pp. 1301-1309, 2003. https://doi.org/10.1109/TCE.2003.1261233
  5. 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, pp. 1209-1221, 2007. https://doi.org/10.1016/j.patrec.2007.02.003
  6. S.D. Chen and A.R. Ramli, "Minimum Mean Brightness Error Bi-Histogram Equalization in Contrast Enhancement," IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, pp. 1310-1319, 2003. https://doi.org/10.1109/TCE.2003.1261234
  7. Z. Yao, Q. Zhou, X. Yang, C. Yang, and Z. Lai, "Quadrants Histogram Equalization with a Clipping Limit for Image Enhancement," Proceeding of International Conference on Wireless Communications and Signal Processing, pp. 1-5, 2016.
  8. C.H. Ooi, N.S.P. Kong, and H. Ibrahim, "Bihistogram Equalization with a Plateau Limit for Digital Image Enhancement," IEEE Transactions on Consumer Electronics, Vol. 55, No. 4, pp. 2072-2080, 2009. https://doi.org/10.1109/TCE.2009.5373771
  9. S.M. Pizer, R.E. Johnston, J.P. Erickson, B.C. Yankaskas, and K.E. Muller, "Contrast Limited Adaptive Histogram Equalization: Speed and Effectiveness," IEEE Conference Publications, pp. 337-345, 1990.
  10. K. Liang, Y. Ma, Y. Xie, B. Zhou, and R. Wang, "A New Adaptive Contrast Enhancement Algorithm for Infrared Images based on Double Plateaus Histogram Equalization," Proceeding of International Conference on Infrared Physics and Technology, Vol. 55, pp. 309-315, 2012.
  11. T. Kim and J. Paik, "Adaptive Contrast Enhancement Using Gain-Controllable Clipped Histogram Equalization," IEEE Transactions on Consumer Electronics, Vol. 54, No. 4, pp. 1803-1810, 2008. https://doi.org/10.1109/TCE.2008.4711238
  12. M.J. Jun and J.J. Lee, "Image Histogram Equalization Based on Gaussian Mixture Model," Journal of Korea Multimedia Society, Vol. 15, No. 6, pp. 748-760, 2012. https://doi.org/10.9717/kmms.2012.15.6.748
  13. A. Rani and R. Kaur, "Image Enhancement using Histogram Equalization," Proceeding of International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, No. 7, pp. 603-606, 2015.
  14. Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli, "Image Quality Assessment: From Error Visibility to Structural Similarity," IEEE Transactions on Image Processing, Vol. 13, No. 4, pp. 600-612, 2004. https://doi.org/10.1109/TIP.2003.819861
  15. J.S. Jeong and Y.J. Kim, "Structural Similarity Index for Image Assessment using Pixel Difference and Saturation Awareness," Journal of KIISE, Vol. 41, No. 10, pp. 847-858, 2014. https://doi.org/10.5626/JOK.2014.41.10.847

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