Analysis of False Color Visualization for HDR Image

HDR영상에서 가색상 시각화 알고리즘 분석

  • Lee, Yong-Hwan (Department of Digital Contents, Wonkwang University) ;
  • Kim, Youngseop (Department of Electronic and Electronical Engineering, Dankook University)
  • 이용환 (원광대학교 디지털콘텐츠공학과) ;
  • 김영섭 (단국대학교 전자전기공학과)
  • Received : 2017.09.12
  • Accepted : 2017.09.22
  • Published : 2017.09.30


High dynamic range (HDR) imaging offers a radically approach of representing colors in digital images. Instead of using the range of colors produced by given devices, HDR imaging method manipulates and stores all colors and brightness levels visible to the human eye. To faithfully represent, store and then reproduce all these effects, the original scene must be stored and treated using high fidelity HDR techniques. Then, tone mapping is required to accommodate HDR image to low dynamic range (LDR) devices, and tone mapping operation of HDR image for realistic display is commonly researched. However, color visualization for analyzing scene luminance in HDR imaging has less attention from researches. This paper presents and implements a method for reproduction and visualization of the false color in HDR images. We produce a color visualization framework with several mapping functions, and evaluate their effectiveness by using RMAE and SNR with commonly used HDR image data. Experiment reveals that the sigmodal mapping function shows better performance in the false color visualization, compared to other methods.



Supported by : 한국연구재단


  1. Rafal K. Mantiuk, Karol Myszkowski, and Hans-Peter Seidel, "High Dynamic Range Imaging", Encyclopedia of Electrical and Electronics Engineering, Wiley, 2016.
  2. Min Chen, Guoping Qiu, Zhibo Chen, and CharlesWang, "JPEG Compatible Coding of High Dynamic Range Imagery using Tone Mapping Operators", Picture Coding Symposium (PCS), 2006.
  3. Thomas Richter, "Backwards Compatible Coding of High Dynamic Range Images with JPEG", Data Compression Conference, 2013.
  4. Shree K. Nayar and Tomoo Mitsunaga, "High Dynamic Range Imaging: Spatially Varying Pixel Exposures", IEEE Conference on Computer Vision and Pattern Recognition, 2000.
  5. Jiang Duan, Guoping Qiu, and Graham Finlayson, "Learning to Display High Dynamic Range Images", IS&Ts Second European Conference on Color in Graphics, Imaging and Vision, 2004.
  6. Francesco Branchitta, Marco Diani, Giovanni Corsini, Antonio Porta, and Marco Romagnoli, "Dynamic Range Compression and Contrast Enhancement in Infrared Imaging Systems", Proceedings of SPIE Electro-Optical and Infrared Systems: Technology and Applications, 2008.
  7. J. Tumblin and H. Rushmeier, "Tone Reproduction for Realistic Images", IEEE Computer Graphics and Applications, vol.13, no. 6, pp.42-48, 1993.
  8. G. Qiu, Y. Mei, K. M. Lam, and M. Qiu, "Tone Mapping HDR Images using Optimization: A General Framework", International Conference on Image Processing, pp.3129-3132, 2010.
  9. Z. Li and J. Zheng, "Visual-Salience-based Tone Mapping for High Dynamic Range Images", IEEE Transactions on Industrial Electronics, vol.61, no.12, pp.7076-7082, 2014.
  10. E. Reinhard, M. Stark, P. Shirley, and J. Ferwerda, "Photographic Tone Reproduction for Digital Images", Conference on Computer Graphics and Interactive Techniques, pp.267-276, 2002.
  11. S. Murray, "Interactive Data Visualization for the Web", O'Reilly Media, 2013.
  13. S. N. Pattanaik, J. A. Ferwerda, M. D. Fairchild, and D. P. Greenberg, "A Multiscale Model of Adaptation and Spatial Vision for Realistic Image Display", Conference on Computer Graphics and Interactive Techniques, pp.287-298, 1998.
  14. A. Pardo and G. Sapiro, "Visualization of High Dynamic Range Images", IEEE Transactions on Image Processing, vol.12, no.6, pp.639-647, 2003.
  15. A. O. Akyuz, "False Color Visualization for HDR Images", International Conference on HDR Imaging, pp.1-5, 2013.
  16. F. Branchitta, M. Diani, G. Corsini, and A. Porta, "New Visualization Method Improves Perception of Details", Electronic Imaging & Signal Processing, pp.1-2, 2008.
  17. E. Reinhard, E. Khan, A. Akyuz, and G. Johnson, "Color Imaging: Fundamentals and Applications", AK Peters Wellesley, 2008.
  19. Peter Ndajah, Hisakazu Kikuchi, Masahiro Yukawa, Hidenori Watanabe, and Shogo Muramatsu, "An Investigation on the Quality of Denoised Images", International Journal of Circuits, Systems and Signal Processing, vol.5, issue.4, pp.423-434, 2011.