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A new histogram equalization method for digital image enhancement and brightness preservation

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Abstract

This paper proposes a new histogram equalization method for effective and efficient mean brightness preservation and contrast enhancement, which prevents intensity saturation and has the ability to preserve image fine details. Basically, the proposed method first separates the test image histogram into two sub-histograms. Then, the plateau limits are calculated from the respective sub-histograms, and they are used to modify those sub-histograms. Histogram equalization is then separately performed on the two sub-histograms to yield a clean and enhanced image. To demonstrate the feasibility of the proposed method, a total of 190 test images are used in simulation and comparison, in which 72 of them are standard test images, while the remainder are made up of real natural images obtained from personal digital camera. The simulation results show that the proposed method outperforms other state-of-the-art methods, both in terms of visual and runtime comparison. Moreover, the simple implementation and fast runtime further underline the importance of the proposed method in consumer electronic products, such as mobile cell-phone, digital camera, and video.

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References

  1. Gonzalez, R.C., Woods, R.E.: Digital image processing, 3rd edn. Prentice, Upper Saddle River, New Jersey (2008)

  2. Chen, S.D., Ramli, A.R.: Minimum mean brightness error bi-histogram equalization in contrast enhancement. IEEE Trans. Consum. Electron. 49(4), 1310–1319 (Nov. 2003)

    Google Scholar 

  3. Kim, M., Chung, M.G.: Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement. IEEE Trans. Consum. Electron. 54(3), 1389–1397 (Aug. 2008)

    Google Scholar 

  4. Sengee, N., Choi, H.K.: Brightness preserving weight clustering histogram equalization. IEEE Trans. Consum. Electron. 54(3), 1329–1337 (Aug. 2008)

    Google Scholar 

  5. Ooi, C.H., Kong, N.S.P., Ibrahim, H.: Bi-histogram equalization with a plateau limit for digital image processing. IEEE Trans. Consum. Electron. 55(4), 2072–2080 (Nov. 2009)

    Google Scholar 

  6. Ooi, C.H., Isa, N.A.M.: Adaptive contrast enhancement methods with brightness preserving. IEEE Trans. Consum. Electron. 56(4), 2543–2551 (Nov. 2010)

    Google Scholar 

  7. Wu, P.C., Cheng, F.C., Chen, Y.K.: A weighting mean-separated sub-histogram equalization for contrast enhancement, Presented at the 2010 international conference on the Biomedical Engineering and Computer Science (ICBECS). Wuhan, China, 23–25 April 2010

  8. Chang, Y.C., Chang, C.M.: A simple histogram modification scheme for contrast enhancement. IEEE Trans. Consum. Electron. 56(2), 737–742 (2010)

    Article  Google Scholar 

  9. http://decsai.ugr.es/cvg/CG/base.htm

  10. http://sipi.usc.edu/database/

  11. Menotti, D., Naiman, L., Facon, J., Araujo, A.A.: Multi-histogram equalization methods for contrast enhancement and brightness preservation. IEEE Trans. Consum. Electron. 53(3), 1186–1194 (Aug. 2007)

    Google Scholar 

  12. Wang, Y., Chen, Q., Zhang, B.: Image enhancement based on equal area dualistic sub-image histogram equalization method. IEEE Trans. Consum. Electron. 45(1), 68–75 (Feb. 1999)

    Google Scholar 

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Authors and Affiliations

  1. School of electrical & Electronic Engineering, Imaging and Intelligent Systems Research Team (ISRT), Universiti Sains Malaysia, Engineering Campus, 14300 , Nibong Tebal, Penang, Malaysia

    Sheng Hoong Lim & Nor Ashidi Mat Isa

  2. Intel Technology (M) Sdn. Bhd., Box 121, Bayan Lepas Free Trade Zone, 11900 , Bayan Lepas, Penang, Malaysia

    Chen Hee Ooi & Kenny Kal Vin Toh

Authors
  1. Sheng Hoong Lim
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  2. Nor Ashidi Mat Isa
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  3. Chen Hee Ooi
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  4. Kenny Kal Vin Toh
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Corresponding author

Correspondence to Nor Ashidi Mat Isa.

Additional information

This work was supported by the Ministry of Science, Technology and Innovation, Malaysia under Science Fund Grant entitled ‘Development of Computational Intelligent Infertility Detection System Based on Sperm Motility Analysis’.

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Lim, S.H., Mat Isa, N.A., Ooi, C.H. et al. A new histogram equalization method for digital image enhancement and brightness preservation. SIViP 9, 675–689 (2015). https://doi.org/10.1007/s11760-013-0500-z

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  • DOI: https://doi.org/10.1007/s11760-013-0500-z

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