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Multimedia Tools and Applications

, Volume 77, Issue 7, pp 8955–8978 | Cite as

Bi-histogram modification method for non-uniform illumination and low-contrast images

  • Teck Long Kong
  • Nor Ashidi Mat Isa
Article
  • 158 Downloads

Abstract

Researchers face non-uniform illumination and low-contrast image challenges during the image-processing stage. A new contrast enhancement method is proposed in this paper to address these challenges. The proposed method first separates the dark and bright regions of an image. Then, these regions are enhanced using two new enhancers, namely, dark and bright. Modified clipped histogram equalization is then applied for contrast enhancement. Finally, the details of the image are added back into the illumination-corrected and contrast-enhanced image for the final output image. Visually, the proposed method successfully produces better images with more uniform illumination and better contrast than the state-of-the-art methods. This claim is supported by quantitative analysis that shows that the proposed method produces the best average measure of enhancement, natural image quality evaluator, and entropy values of 797 test images compared with other state-of-the-art methods.

Keywords

Non-uniform illumination Image enhancement Contrast Histogram Entropy 

Notes

Acknowledgements

This project entitled “Formulation of a robust framework of image enhancement for non-uniform illumination and low-contrast images” is supported by the Fundamental Research Grant Scheme of the Ministry of Education, Malaysia.

References

  1. 1.
    Acharya T, Ray AK (2005) Image processing: principles and applications. John Wiley & Sons, HobokenGoogle Scholar
  2. 2.
    Agaian SS, Panetta K, Grigoryan AM (2000) A new measure of image enhancement. In IASTED International Conference on Signal Processing & Communication (pp 19–22). CiteseerGoogle Scholar
  3. 3.
    Bovik AC (2009) The essential guide to image processing, 2nd edn. Academic Press, BostonGoogle Scholar
  4. 4.
    Chaira T, Ray AK (2009) Fuzzy image processing and applications with MATLAB. CRC Press, Boca RatonGoogle Scholar
  5. 5.
    Dippel S, Stahl M, Wiemker R, Blaffert T (2002) Multiscale contrast enhancement for radiographies: Laplacian pyramid versus fast wavelet transform. IEEE Trans Med Imaging 21(4):343–353CrossRefGoogle Scholar
  6. 6.
    Gonzalez RC, Wintz P (1987) Digital image processing, 1987. Addison–Wesley, ReadingzbMATHGoogle Scholar
  7. 7.
    Hasikin K, Isa NAM (2012) Fuzzy enhancement for nonuniform illumination of microscopic Sprague Dawley rat sperm image. In Medical Measurements and Applications Proceedings (MeMeA), 2012 I.E. International Symposium on (pp 1–6). IEEE. doi: 10.1109/MeMeA.2012.6226623
  8. 8.
    Hasikin K, Isa NAM (2013) Fuzzy image enhancement for low contrast and non-uniform illumination images. In Signal and Image Processing Applications (ICSIPA), 2013 I.E. International Conference on (pp 275–280). IEEE. doi: 10.1109/ICSIPA.2013.6708017
  9. 9.
    Hasikin K, Isa NAM (2014) Adaptive fuzzy contrast factor enhancement technique for low contrast and nonuniform illumination images. SIViP 8(8):1591–1603CrossRefGoogle Scholar
  10. 10.
    Jiao L, Sun Z, Sha A (2009) Local image contrast enhancement under non-uniform illumination. In Technology and Innovation Conference 2009 (ITIC 2009), International (pp 1–5). IET. doi: 10.1049/cp.2009.1520
  11. 11.
    Jobson DJ, Rahman Z-U, Woodell GA (1997) Properties and performance of a center/surround retinex. IEEE Trans Image Process 6(3):451–462CrossRefGoogle Scholar
  12. 12.
    Jobson DJ, Rahman Z-U, Woodell GA (1997) A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans Image Process 6(7):965–976CrossRefGoogle Scholar
  13. 13.
    Kim T, Paik J (2008) Adaptive contrast enhancement using gain-controllable clipped histogram equalization. IEEE Trans Consum Electron 54(4):1803–1810CrossRefGoogle Scholar
  14. 14.
    Kim J-Y, Kim L-S, Hwang S-H (2001) An advanced contrast enhancement using partially overlapped sub-block histogram equalization. IEEE Trans Circuits Syst Video Technol 11(4):475–484CrossRefGoogle Scholar
  15. 15.
    Lamberti F, Montrucchio B, Sanna A (2006) CMBFHE: a novel contrast enhancement technique based on cascaded multistep binomial filtering histogram equalization. IEEE Trans Consum Electron 52(3):966–974CrossRefGoogle Scholar
  16. 16.
    Land EH, McCann J (1971) Lightness and retinex theory. JOSA 61(1):1–11CrossRefGoogle Scholar
  17. 17.
    Lee E, Kim S, Kang W, Seo D, Paik J (2013) Contrast enhancement using dominant brightness level analysis and adaptive intensity transformation for remote sensing images. IEEE Geosci Remote SensLett 10(1):62–66CrossRefGoogle Scholar
  18. 18.
    Leung C-C, Chan K-S, Chan H-M, Tsui W-K (2005) A new approach for image enhancement applied to low-contrast–low-illumination IC and document images. Pattern Recogn Lett 26(6):769–778CrossRefGoogle Scholar
  19. 19.
    Liang K, Ma Y, Xie Y, Zhou B, Wang R (2012) A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization. Infrared Phys Technol 55(4):309–315CrossRefGoogle Scholar
  20. 20.
    Lin H, Shi Z (2014) Multi-scale retinex improvement for nighttime image enhancement. Optik-International Journal for Light and Electron Optics 125(24):7143–7148CrossRefGoogle Scholar
  21. 21.
    Liu B, Jin W, Chen Y, Liu C, Li L (2011) Contrast enhancement using non-overlapped sub-blocks and local histogram projection. IEEE Trans Consum Electron 57(2):583–588CrossRefGoogle Scholar
  22. 22.
    Liu H-D, Yang M, Gao Y, Cao L (2014) Fast local histogram specification. IEEE Trans Circuits Syst Video Technol 24(11):1833–1843CrossRefGoogle Scholar
  23. 23.
    Magudeeswaran V, Ravichandran C (2013) Fuzzy logic-based histogram equalization for image contrast enhancement. Math Probl Eng 2013Google Scholar
  24. 24.
    Mittal A, Soundararajan R, Bovik AC (2013) Making a “completely blind” image quality analyzer. IEEE Signal Process Lett 20(3):209–212CrossRefGoogle Scholar
  25. 25.
    Nafornita C, Isar A (2014) Wavelet based contrast enhancement for still images. In Electronics and Telecommunications (ISETC), 2014 11th International Symposium on (pp 1–4). IEEE. doi: 10.1109/ISETC.2014.7010797
  26. 26.
    Panetta K, Wharton EJ, Agaian SS (2008) Human visual system-based image enhancement and logarithmic contrast measure. IEEE Trans Syst Man Cybern Part B: Cybern 38(1):174–188CrossRefGoogle Scholar
  27. 27.
    Pizer SM, Amburn EP, Austin JD, Cromartie R, Geselowitz A, Greer T et al (1987) Adaptive histogram equalization and its variations. Computer Vision, Graphics, and Image Processing 39(3):355–368CrossRefGoogle Scholar
  28. 28.
    Rahman ZU, Jobson DJ, Woodell GA (1996) Multi-scale retinex for color image enhancement. In Image Processing, 1996. Proceedings., International Conference on (Vol. 3, pp 1003–1006). IEEE.Google Scholar
  29. 29.
    Raju G, Nair MS (2014) A fast and efficient color image enhancement method based on fuzzy-logic and histogram. AEU-Int J Electron Commun 68(3):237–243CrossRefGoogle Scholar
  30. 30.
    Rubin SH, Kountchev R, Todorov V, Kountcheva R (2006) Contrast enhancement with histogram-adaptive image segmentation. In Information Reuse and Integration, 2006 I.E. International Conference on (pp 602–607). IEEE. doi: 10.1109/IRI.2006.252482
  31. 31.
    Rumsey DJ, Unger D (2015) U Can: statistics for dummies. John Wiley & Sons, HobokenGoogle Scholar
  32. 32.
    Russ JC (2006) The image processing handbook, 4th edn. CRC Press, Boca RatonGoogle Scholar
  33. 33.
    Shannon CE (2001) A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review 5(1):3–55MathSciNetCrossRefGoogle Scholar
  34. 34.
    Sridhar S (2011) Digital Image Processing. Oxford University Press, India, 640 pGoogle Scholar
  35. 35.
    Wan Y, Shi D (2007) Joint exact histogram specification and image enhancement through the wavelet transform. IEEE Trans Image Process 16(9):2245–2250MathSciNetCrossRefGoogle Scholar
  36. 36.
    Wang Y, Chen Q, Zhang B (1999) Image enhancement based on equal area dualistic sub-image histogram equalization method. IEEE Trans Consum Electron 45(1):68–75CrossRefGoogle Scholar
  37. 37.
    Wang C, Li Y, Wang C (2008) An efficient illumination compensation based on plane-fit for face recognition. In Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on (pp 939–943). IEEE. doi: 10.1109/ICARCV.2008.4795644
  38. 38.
    Wang S, Zheng J, Hu H-M, Li B (2013) Naturalness preserved enhancement algorithm for non-uniform illumination images. IEEE Trans Image Process 22(9):3538–3548CrossRefGoogle Scholar
  39. 39.
    Weber M (1999) Faces 1999 (front). Computational vision at CALTECH. http://www.Vision.Caltech.Edu/Image_Datasets/faces/faces.Tar. Accessed 14/4/2015 2015
  40. 40.
    Wei W (2013) Image binarization under non-uniform illumination based on gray-intensity wave equalization. Image and Signal Processing (CISP), 2013 6th International Congress. p. 604–9. doi: 10.1109/cisp.2013.6745238
  41. 41.
    Welinder P (2010) Pasadena buildings 2010 [Online]. Computational vision at CALTECH. Available: http://www.vision.caltech.edu/image_datasets/pasadena-buildings.zip. Accessed 14 Apr 2015
  42. 42.
    Wharton E, Panetta K, Againan S (2007) Human visual system based multi-histogram equalization for non-uniform illumination and shoadow correction. In Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on (Vol. 1, pp I–729). IEEE. doi: 10.1109/ICASSP.2007.366011
  43. 43.
    You X, Du L, Cheung Y, Chen Q (2010) A blind watermarking scheme using new Nontensor product wavelet filter banks. IEEE Trans Image Process 19(12):3271–3284MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Imaging and Intelligent Systems Research Team (ISRT), School of Electrical and Electronic Engineering, Engineering CampusUniversiti Sains MalaysiaPenangMalaysia

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