Journal of IKEEE (전기전자학회논문지)

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

DOI QR Code

A Laplace Pyramid Fusion Method for Low Light and Backlit Images using 2 Virtual Images

2개의 가상영상을 사용하는 저조도 및 역광영상의 라플라스 피라미드 융합 기법

  • Jin Heon Kim (Dept. of Computer Engineering, Seokyeong University)
  • Received : 2023.06.07
  • Accepted : 2023.06.27
  • Published : 2023.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This paper introduces a method to improve the contrast of images taken in backlit in low light by fusing two virtual images representing the dark and bright areas using Laplacian pyramid. The proposed technique automatically adjusts histogram stretching and gamma conversion parameters according to the images through histogram analysis when creating two virtual images. In Laplace fusion process, a method of using only grayscale values as weights is presented, and NIQA indicators were calculated using two standard image data sets to demonstrate its effectiveness. The proposed technique uses a virtual image generation method that can be implemented as a LUT, simplifies the creation of a weight map, and has the advantage of less computational burden because one-channel fusion is possible.

본 논문에서는 역광 촬영된 사진이나 저조도에서 찍힌 사진을 어두운 영역과 밝은 영역을 대표하는 두 장의 가상 영상으로 라플라시안 피라미드로 융합하여 영상의 대조비를 개선하는 방안에 대하여 소개한다. 제안된 기법은 두 장의 가상 영상을 만들 때 히스토그램 분석을 통해 히스토그램 스트레칭과 감마변환 파라미터를 영상에 따라 자동으로 조절한다. 라플라스 융합과정에서 가중치를 계조값만을 사용하는 방법을 제시하고 2종의 표준 영상 데이터 세트를 사용하여 NIQA 지표를 산출하여 그 효용성을 보인다. 제안된 기법은 LUT로 구현 가능한 가상영상 생성 방법을 사용하였으며 가중치 맵 생성을 단순화하였고 1채널 융합이 가능하여 연산 부담이 적은 장점이 있다.

Keywords

Acknowledgement

This Research was supported by Seokyeong University in 2021.

References

  1. 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
  2. Gang, Seok-Ju, "High Dynamic Range Imaging technology and recent trends," Information Display, Vol.20, No.3, pp.3-9, 2019.
  3. Mertens T, Kautz J, Reeth FV. "Exposure fusion," Proceedings of the 15th Pacific conference on computer graphics and applications, pp.382-390, 2007.
  4. T. Mertens, J. Kautz and F. Van Reeth1, "Exposure Fusion:A Simple and Practical Alternative to High Dynamic Range Photography," Computer Graphics Forum, vol.28, no.1 pp.161-171, 2009. DOI: 10.1111/j.1467-8659.2008.01171.x
  5. 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
  6. Saleem, A., Beghdadi, A. & Boashash, B. "Image fusion-based contrast enhancement," J Image Video Proc 2012, 2012. DOI: 10.1186/1687-5281-2012-10
  7. Charles Hessel, Jean-Michel Morel, "An Extended Exposure Fusion and its Application to Single Image Contrast Enhancement," Proc. IEEE/CVF WACV, pp.137-146, 2020. DOI: 10.1109/WACV45572.2020.9093643
  8. W. Wang, X. Wu, X. Yuan and Z. Gao, "AnExperiment-Based Review of Low-Light Image Enhancement Methods," IEEE Access, vol.8, pp. 87884-87917, 2020. DOI: 10.1109/ACCESS.2020.2992749
  9. matlab help center,imadjust, https://kr.mathworks.com/help/images/ref/imadjust.html
  10. V. Bychkovsky, S. Paris, E. Chan, and F. Durand, "Learning photographic global tonal adjustment with a database of input/output image pairs," IEEE in CVPR, pp.97-104, 2011. DOI: 10.1109/CVPR.2011.5995332
  11. MIT-Adobe FiveK Dataset, URL: https://data.csail.mit.edu/graphics/fivek/
  12. 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
  13. Z. Li, "Li's Database," https://github.com/7thChord/backlit
  14. Zuiderveld K., "Contrast limited adaptive histogram equalization," Graphics gems IV, 474-485, 1994. https://doi.org/10.1016/B978-0-12-336156-1.50061-6
  15. Hasler, D., & Suesstrunk, S. E. "Measuring colorfulness in natural mages," Human Vision and Electronic Imaging VIII, 2003. DOI: 10.1117/12.477378
  16. 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
  17. 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
  18. 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. https://doi.org/10.1109/LSP.2012.2227726
  19. Anish Mittal, "NIQE Software" https://github.com/csjunxu/Bovik_NIQE_SPL2013