A Comparative Study of Various Tone Mapping Methods

Authors: YasirSalih, AamirSaeed Malik, Wazirahbt.Md-Esa

Abstract:

In the recent years, high dynamic range imaging has gain popularity with the advancement in digital photography. In this contribution we present a subjective evaluation of various tone production and tone mapping techniques by a number of participants. Firstly, standard HDR images were used and the participants were asked to rate them based on a given rating scheme. After that, the participant was asked to rate HDR image generated using linear and nonlinear combination approach of multiple exposure images. The experimental results showed that linearly generated HDR images have better visualization than the nonlinear combined ones. In addition, Reinhard et al. and the exponential tone mapping operators have shown better results compared to logarithmic and the Garrett et al. tone mapping operators.

Keywords: tone mapping, high dynamic range, low dynamic range, bits per pixel.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072644

References:

[1] E. Reinhard, G. Ward, S. Pattanaik, and P. Debevec, High dynamic range imaging acquisition, display and image-based lighting, 1st ed. San Francisco: Morgan Kaufmann Publisher, An imprint of Elsevier, 2005, pp. 115-164.
[2] J. Duan, M. Berssan, C. Dance, and G. Qiu, "Tone-mapping high dynamic range images by novel histogram adjustment," Pattern Recognition, vol. 43, no. 5, pp. 1847-1862, May. 2010.
[3] A. Vavilin, K. Deb, and K.-hyun Jo, "Fast HDR Image Generation Technique Based on Exposure Blending," in Trends in Applied Intelligent Systems, 2010, pp. 379-388.
[4] T. Jinno, M. Okuda, and N. Adami, "Acqusition and encoding of high dynamcirnage images using inverse tone mappoing," in Interantional Conference Image Processing, 2007, pp. 181-184 Vol.4.
[5] K.-H. Jo and A. Vavilin, "HDR Image Generation based on Intensity Clustering and Local Feature Analysis," Computers in Human Behavior, Nov. 2010.
[6] B. Lim, R.-hong Park, and S. Kim, "High dynamic range for contrast enhancement," IEEE Transactions on Consumer Electronics, vol. 52, no. 4, pp. 1454-1462, Nov. 2006.
[7] A. Vavilin and K.-hyun Jo, "Recursive HDR image generation from differently exposed images based on local image properties," in International Conference on Control, Automation and Systems, 2008, pp. 2791-2796.
[8] Y. Bandoh, G. Qiu, M. Okuda, S. Daly, T. Ach, and O. C. Au, "Recent advance in high dynamic range imaging technology," in IEEE 17th International Conference on Image Processing September, 2010, pp. 3125-3128.
[9] Z. Guangjun and L. Yan, "An improved tone mapping algorithm for high dynamic range images," in International Conference on Computer Application and System Modeling, 2010, no. Iccasm, pp. 466-468 Vol.2.
[10] X. Li, K. M. Lam, and L. Shen, "An adaptive algorithm for the display of high-dynamic range images," Journal of Visual Communication and Image Representation, vol. 18, no. 5, pp. 397-405, Oct. 2007.
[11] A. Pardo and G. Sapiro, "Visulaization of high dynamic range images," in International Conference on Computer Vision, 2002, pp. 633-636 Vol.1.
[12] M. Čadík, M. Wimmer, L. Neumann, and A. Artusi, "Evaluation of HDR tone mapping methods using essential perceptual attributes," Computers & Graphics, vol. 32, no. 3, pp. 330-349, Jun. 2008.
[13] W.-ho Cho and K.-S. Hong, "Extending dynamic range of two color images under different exposures," in Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004, pp. 853-856 Vol.4.
[14] P. E. Debevvec and J. Malik, "Recovering High Dynamic Range Radiance Maps from Photographs," in ACM SIGGRAPH Conference on Computer Graphics, 2008, pp. 369-378.
[15] E. Reinhard, M. Stark, P. Shirley, and J. Ferwerda, "Photographic tone reproduction for digital images," ACM Transactions on Graphics, vol. 21, no. 3, Jul. 2002.
[16] G. M. Johnson and M. D. Fairchild, "Rendering HDR images," in IS and T/SID Color Imaging Conference, 2003, pp. 36-41. M. Young, TheTechincal Writers Handbook. Mill Valley, CA: University Science, 1989.
[17] YasirSalih, Aamir S. Malik, "Comparison of Stochastic Filtering Methods for 3D Tracking", 2011 Pattern Recognition 44 (10-11), pp. 2711-2737, March 2011.
[18] YasirSalih, Aamir S. Malik, Zazilah May, "Depth Estimation Using Monocular Cues from Single Image", 2011 National Postgraduate Conference (NPC 2011), UTP, Perak, Malaysia, 19-20 September 2011.
[19] YasirSalih, Aamir S. Malik, "3D Object Tracking Using Three Kalman Filters" , 2011 IEEE Symposium of Computer & Informatics (ISCI 2011), Kuala Lumpur, Malaysia, 20-22 March 2011.
[20] YasirSalih, Aamir S. Malik, "3D Tracking Using Particle Filters" , 2011 International Instrumentation and Measurement Technology Conference (I2MTC 2011), Binjiang, Hangzhau, China, 10-12 May 2011.
[21] YasirSalih, Aamir S. Malik, "Stochastic Filters for Object Tracking", 2011 the 15th IEEE Symposium on Consumer Electronics (ISCE 2011), Singapore, 14-17 June 2011.
[22] Ramli, R., Malik, A. S., Hani, A. F. M. and Jamil, A. (2011), Acne analysis, grading and computational assessment methods: an overview, Skin Research and Technology, 17: no. doi: 10.1111/j.1600- 0846.2011.00542.x