Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
권호 표지
DOI QR코드

DOI QR Code

An Enhancement Technique for Backlit Images using Laplace Pyramid Fusion

라플라스 피라미드 융합을 이용한 역광영상의 개선 방법

  • Kim, Jin Heon (Dept. of Computer Engineering, Seokyeong University)
  • Received : 2022.06.13
  • Accepted : 2022.06.23
  • Published : 2022.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

There is a limit to improving the image quality through global processing of images taken under backlighting because too bright and dark parts are mixed in one scene. This paper introduces a method to improve the quality of a photo by making two virtual images that improve the dark and bright areas of a backlit photo, and fusing them with the original image into a Laplacian pyramid. The proposed method reduces the computational burden by using histogram stretching and gamma transformation that can be simplified with LUT when creating the two virtual images. In addition, in order to obtain a color-enhanced image, contrast conversion was performed only on the luminance using the HSV coordinate system. The proposed technique showed its effectiveness by calculating several NIQA indicators using standard image data sets.

역광 조명에서 촬영된 영상은 한 장면에 지나치게 밝은 부분과 어두운 부분이 혼재되어 있어서 이를 전역적인 처리로 화질을 개선하는데는 한계가 있다. 본 논문은 역광 촬영된 사진을 각각 어두운 영역과 밝은 영역을 개선하는 두 장의 가상 영상으로 만들어 이를 원본 영상과 함께 라플라시안 피라미드로 융합하여 사진의 품질을 개선하는 방안에 대해 소개한다. 제안된 기법은 두 장의 가상 영상을 만들 때 LUT로 단순화할 수 있는 히스토그램 스트레칭과 감마변환을 활용하여 연산 부담을 저감하였다. 또한 색상 강화된 영상을 얻기 위해 HSV 좌표계를 사용하여 휘도에 대해서만 명암 변환을 실시하였다. 제안된 기법은 표준 영상 데이터 세트를 사용하여 몇 가지의 NIQA 지표를 산출하여 그 효용성을 보였다.

Keywords

Acknowledgement

This Research was supported by Seokyeong University in 2020.

References

  1. David C. C. Wang, Anthony H. Vagnucci and, C. C. Li, "Digital image enhancement: A survey," Computer Vision, Graphics, and Image Processing, vol.24 no.3, pp.363-381, 1983. DOI: 10.1016/0734-189X(83)90061-0
  2. Rafael Gonzalez and Richard Woods, Digital Image Processing, 2nd edition, Addison-Wesley Pub, 2002.
  3. Rahman S, RahmanM M, Abdullah-Al-Wadud M, et al. "An adaptive gamma correction for image enhancement," Eurasip Journal on Image and Video Processing, vol.1, no.35, 2016. DOI: 10.1186/s13640-016-0138-1
  4. Manpreet Kaur, Jasdeep Kaur and Jappreet Kaur, "Survey of Contrast Enhancement Techniques based on Histogram Equalization," International Journal of Advanced Computer Science and Applications, vol.2 no.7, 2011. DOI: 10.14569/IJACSA.2011.020721
  5. Y.-T. Kim, "Contrast enhancement using brightness preserving bihistogram equalization," IEEE Trans. Consum. Electron., vol.43, no.1, pp.18, 1997. DOI: 10.1109/30.580378
  6. B. Liu, W. Jin, Y. Chen, C. Liu, and L. Li, "Contrast enhancement using non-overlapped sub-blocks and local histogram projection," IEEE Trans. Consum. Electron., vol.57, no.2, pp.583588, 2011. DOI: 10.1109/TCE.2011.5955195
  7. Zuiderveld K., "Contrast limited adaptive histogram equalization," Graphics gems IV, pp.474-485, 1994.
  8. E. H. Land and J. J. McCann, "Lightness and Retinex theory," J. Opt. Soc. Amer., vol.61, no.1, pp.111, 1971. DOI: 10.1364/JOSA.61.000001
  9. D. J. Jobson, Z. Rahman, and G. A. Woodell, "Properties and performance of a center/surround retinex," IEEE Trans. Image Processing, vol.6, no.3, pp.451-462, 1997. DOI: 10.1109/83.557356
  10. D. J. Jobson, Z. Rahman, and G. A. Woodell, "A multiscale retinex for bridging the gap between color images and the human observation of scenes," IEEE Trans. Image Processing, vol.6, no.7, pp.965-976, 2002. DOI: 10.1109/83.597272
  11. D. J. Jobson, "Retinex processing for automatic image enhancement," J. Electron. Imag., vol.13, no.1, pp.100-110, 2004. DOI: 10.1117/12.469537
  12. Syed Zaheeruddin and K. Suganthib, "Image Contrast Enhancement by Homomorphic Filtering based Parametric Fuzzy Transform," International Conference on Recent Trends in Advanced Computing ICRTAC, 2019. DOI: 10.1016/j.procs.2020.01.095
  13. T. Sun, C. Jung, P. Ke, H. Song, and J. Hwang, "Readability enhancement of low light videos based on discrete wavelet transform," Proc. IEEE Int. Symp. Multimedia, pp.342-345, 2017. DOI: 10.1109/ISM.2017.63
  14. B. Xu, D. Zhou and W. Li, "Image Enhancement Algorithm Based on GAN Neural Network," IEEE Access, vol.10, pp.36766-36777, 2022. DOI: 10.1109/ACCESS.2022.3163241
  15. J. Li, X. Feng and Z. Hua, "Low-Light Image Enhancement via Progressive-Recursive Network," IEEE Transactions on Circuits and Systems for Video Technology, vol.31, no.11, pp.4227-4240, 2021. DOI: 10.1109/TCSVT.2021.3049940
  16. Mertens T, Kautz J, Reeth FV. "Exposure fusion," Proceedings of the 15th Pacific conference on computer graphics and applications, pp.382-390, 2007.
  17. T. Mertens, J. Kautz and F. Van Reeth1, "Exposure Fusion:A Simple and Practical Alternative to High Dynamic Range Photography," Computer Graphics Forum, Blackwell Publishing, vol.28, no.1 pp.161-171, 2009. DOI: 10.1111/j.1467-8659.2008.01171.x
  18. P. J. Burt, and E. H. Adelson, "The Laplacian Pyramid as a Compact Image Code," IEEE Trans. Commun., vol.31, no.4, pp.532-540, 1983. DOI: 10.1109/TCOM.1983.1095851
  19. "High Dynamic Range," https://en.wikipedia.org/wiki/High_dynamic_range
  20. S. Yun, J. H. Kim and S. Kim, "Image enhancement using a fusion framework of histogram equalization and laplacian pyramid," IEEE Transactions on Consumer Electronics, vol.56, no.4, pp.2763-2771, 2010. DOI: 10.1109/TCE.2010.5681167
  21. W. Wang, X. Wu, X. Yuan and Z. Gao, "An Experiment-Based Review of Low-Light Image Enhancement Methods," IEEE Access, vol.8, pp. 87884-87917, 2020. DOI: 10.1109/ACCESS.2020.2992749
  22. T. Trongtirakul, W. Chiracharit and S. S. Agaian, "Single Backlit Image Enhancement," IEEE Access, vol. 8, pp.71940-71950, 2020. DOI: 10.1109/ACCESS.2020.2987256
  23. Z. Li, "Li's Database," https://github.com/7thChord/backlit
  24. Hasler, D., & Suesstrunk, S. E. "Measuring colorfulness in natural mages," Human Vision and Electronic Imaging VIII, 2003.
  25. M. A. Qureshi, A. Beghdadi, and M. Deriche, "Towards the design of a consistent image contrast enhancement evaluation measure," Signal Process., Image Commun., vol.58, pp.212-227, 2017. DOI: 10.1016/j.image.2017.08.004
  26. T. Celik and T. Tjahjadi, "Automatic Image Equalization and Contrast Enhancement Using Gaussian Mixture Modeling," IEEE Transactions on Image Processing, vol.21, no.1, pp.145-156, 2012. DOI: 10.1109/TIP.2011.2162419
  27. A. Mittal, R. Soundararajan and A. C. Bovik, "Making a "Completely Blind" Image Quality Analyzer," IEEE Signal Processing Letters, vol.20, no.3, pp.209-212, 2013. DOI: 10.1109/LSP.2012.2227726
  28. Anish Mittal, "NIQE Software" https://github.com/csjunxu/Bovik_NIQE_SPL2013
  29. Li C, Zhu J, Bi L, Zhang W, Liu Y, "A low-light image enhancement method with brightness balance and detail preservation," PLOS ONE, Vol.17, No.5, pp.e0262478. DOI: 10.1371/journal.pone.0262478