Image Tone Mapping for an HDR Image by Adoptive Global tone-mapping algorithm

International Journal of Electronics and Communication Engineering
© 2015 by SSRG - IJECE Journal
Volume 2 Issue 8
Year of Publication : 2015
Authors : Subodh Prakash Tiwari and Ashutosh Shrivastava
pdf
How to Cite?

Subodh Prakash Tiwari and Ashutosh Shrivastava, "Image Tone Mapping for an HDR Image by Adoptive Global tone-mapping algorithm," SSRG International Journal of Electronics and Communication Engineering, vol. 2,  no. 8, pp. 4-8, 2015. Crossref, https://doi.org/10.14445/23488549/IJECE-V2I8P103

Abstract:

It is the age of fast and good quality Digital images, those are subject to blurring due to many hardware limitations, such as atmospheric disturbance, apparatus noise and poor focus quality. Visual saliency aims to predict the attentional steady intent look of observers viewing a scene, and therefore tone mapping of high dynamic range (HDR) images concept is highly useful for it. The work has focused on incorporation of saliency-aware weighting and edge-aware weighting into local tone-mapping algorithms for HDR images. The visual quality of the tone-mapped resultant image, especially the attention-salient areas, will be improved by the saliency-aware weighting. Experiments show that the proposed global scale tone mapping technique produces good results on a variety of high dynamic range images.

Keywords:

 HDR Imaging, Exposure Determination, Tone mapping, local filtering

References:

[1] P. E. Debevec and J. Malik, “Rendering high dynamic range radiance maps from photographs,” in Proc. SIGGRAPH, Los Angeles, CA, USA, Aug. 1997, pp. 369–378.
[2] S. Grgic, M. Grgic, and B. Zovko-Cihlar, “Performance analysis of image compression using wavelets,” IEEE Trans. Ind. Electron., vol. 48, no. 3,pp. 682–695, Jun. 2001.
[3] J. Garcia et al., “Directional people counter based on head tracking,” IEEE Trans. Ind.Electron., vol. 60, no. 9, pp. 3991–4000, Sep. 2013.
[4] J. DiCarlo and B. Wandell, “Rendering high dynamic range images”, Proc. SPIE, vol.3965, pp. 392 – 401, 2001
[5] J. Tumblin and H. Rushmeier, “Tone reproduction for realistic images”, IEEE Computer Graphics and Applications, vol. 13, pp. 42– 48, 1993
[6] M. Ashikhmin, “A tone mapping algorithm for high contrast images”, Proc. Euro graphics Workshop on Rendering, P. Debevec and S. Gibson Eds., pp. 1 – 11, 2002
[7] G. W. Larson, H. Rushmeier and C. Piatko, “A visibility matching tone reproduction operator for high dynamic range scenes”, IEEE Trans on Visualization and Computer Graphics, vol. 3, pp. 291 – 306, 1997
[8] J. Duan, G. Qiu and G. D. Finlayson, "Learning to display high dynamic range images", CGIV'2004, IS&T's Second European Conference on Color in Graphics, Imaging and Vision, Aachen, Germany, April 5-8, 2004J.
[9] J. Duan and G. Qiu, "Fast tone mapping for high dynamic range images", ICPR2004,17th International Conference on Pattern Recognition, Cambridge, United Kingdom, 23 - 26 August 2004
[10] E. Reinhard, M. Stark, P. Shirley and J. Ferwerda, “Photographic tone reproduction for digital images”, Proc. ACM SIGGRAPH’2002
[11] R. Fattal, D. Lischinski and M. Werman, “Gradient domain high dynamic range compression”, Proc. ACM SIGGRAPH’2002
[12] K. He, J. Sun, and X. Tang, “Guided image filtering,” IEEE Trans. Pattern Anal. Mach. Learn., vol. 35, no. 6, pp. 1397–1409, Jun. 2013.
[13] L. Itti, C. Koch, and E. Niebur, “Amodel of saliency-based visual attention for rapid scene analysis,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 11, pp. 1254–1259, Nov. 1998.
[14] S. Lu and J. H. Lim, “Saliency modeling from image histograms,” in Proc. 12th Eur. Conf. Comput. Vis., Florence, Italy, Oct. 2012, pp. 321–332.