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A Suitable LDR Image from HDR by CIELAB Based Tone-Mapping Algorithm

Arpna Patel1 , Ratnesh Dubey2 , Vineet Richhariya3

Section:Research Paper, Product Type: Journal Paper
Volume-3 , Issue-7 , Page no. 139-143, Jul-2015

Online published on Jul 30, 2015

Copyright © Arpna Patel, Ratnesh Dubey, Vineet Richhariya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Arpna Patel, Ratnesh Dubey, Vineet Richhariya, “A Suitable LDR Image from HDR by CIELAB Based Tone-Mapping Algorithm,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.7, pp.139-143, 2015.

MLA Style Citation: Arpna Patel, Ratnesh Dubey, Vineet Richhariya "A Suitable LDR Image from HDR by CIELAB Based Tone-Mapping Algorithm." International Journal of Computer Sciences and Engineering 3.7 (2015): 139-143.

APA Style Citation: Arpna Patel, Ratnesh Dubey, Vineet Richhariya, (2015). A Suitable LDR Image from HDR by CIELAB Based Tone-Mapping Algorithm. International Journal of Computer Sciences and Engineering, 3(7), 139-143.

BibTex Style Citation:
@article{Patel_2015,
author = {Arpna Patel, Ratnesh Dubey, Vineet Richhariya},
title = {A Suitable LDR Image from HDR by CIELAB Based Tone-Mapping Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2015},
volume = {3},
Issue = {7},
month = {7},
year = {2015},
issn = {2347-2693},
pages = {139-143},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=590},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=590
TI - A Suitable LDR Image from HDR by CIELAB Based Tone-Mapping Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - Arpna Patel, Ratnesh Dubey, Vineet Richhariya
PY - 2015
DA - 2015/07/30
PB - IJCSE, Indore, INDIA
SP - 139-143
IS - 7
VL - 3
SN - 2347-2693
ER -

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Abstract

This paper presents an analysis of the CIELAB color feature based tone mapping technique. After analysis of these techniques we had concluded that saliency based tone mapping algorithm is not computationally efficient as good as the proposed methodology. There is different Salience-based Tone mapping methods for High dynamic range images that have the halo artifacts significantly reduced. The visual quality of tone-mapped image, especially based on salient regions, is enhanced by the saliency-aware weighting. Experimental results show that the proposed method produce good results on a variety of high dynamic range images as saliency-aware technique. The proposed method is more computational efficient and the visual quality of the proposed method is also improved as of saliency based tone mapping.

Key-Words / Index Term

CIELAB Colour Space; Tone Mapping; HDR Image; Weighted Least Square Filter

References

[1] Zhengguo Li and Jinghong Zheng “Visual-Salience-Based Tone Mapping for High Dynamic Range Images” IEEE Transactions on Industrial Electronics, Vol. 61, No. 12, December 2014,PP. 7076-7082
[2] J. Garcia et al., “Directional people counter based on head tracking,” IEEE Trans. Ind. Electron., vol. 60, no. 9, Sep. 2013, pp. 3991–4000.
[3] A. Borji, D. N. Sihite, and L. Itti, “Quantitative analysis of humanmodel agreement in visual saliency modeling: A comparative study,” IEEE Trans. Image Process., vol. 22, no. 1, Jan. 2013, pp. 55–69.
[4] C. Y. Chang and H. Lie, “Real-time visual tracking and measurement to control fast dynamics of overhead cranes,” IEEE Trans. Ind. Electron., vol. 59, no. 3, Mar. 2012, pp. 1640–1649.
[5] H. L. Zhuang, K. S. Low, and W. Y. Yau, “Multichannel pulse-coupledneural network-based color image segmentation for object detection,” IEEE Trans. Ind. Electron., vol. 59, no. 8, Aug. 2012, pp. 3299–3308.
[6] S. Y. Chen, G. J. Luo, X. Li, S. M. Ji, and B. W. Zhang, “The specular exponent as a criterion for appearance quality assessment of pearllike objects by artificial vision,” IEEE Trans. Ind. Electron., vol. 59, no. 8, Aug. 2012, pp. 3264–3272
[7] J. Li, Y. H. Tian, T. J. Huang, and W. Gao, “Probabilistic multi-task learning for visual saliency estimation in video,” Int. J. Comput. Vis., vol. 90, no. 2, Nov. 2010, pp. 150–165.
[8] P. Y. Hsiao, C. L. Lu, and L. C. Fu, “Multilayered image processing for multiscale Harris corner detection in digital realization,” IEEE Trans. Ind. Electron., vol. 57, no. 5, , May 2010, pp. 1799–1805.
[9] Z. Farbman, R. Fattal, D. Lischinski, and R. Szeliski, “Edge-preserving decompositions for multi-scale tone and detail manipulation,” ACM Trans. Graphics, vol. 21, no. 3, Aug. 2008, pp. 249–256.
[10] E. Reinhard, G. Ward, S. Pattanaik, and P. E. Debevec, High Dynamic Range Imaging: Acquisition, Display and Image-Based Lighting. San Mateo, CA, USA: Morgan Kaufmann, 2005.
[11] R. Fattal, D. Lischinski, and M.Werman, “Gradient domain high dynamic range compression,” ACMTrans. Graphics, vol. 27, no. 3, Jul. 2002, pp. 67:1–67:10.
[12] E. Reinhard, M. Stark, P. Shirley, and J. Ferwerda, “Photographic tone reproduction for digital images,” ACM Trans. Graphics, vol. 21, no. 3, , Jul. 2002, pp. 267–276.
[13] S. Grgic, M. Grgic, and B. Zovko-Cihlar, “Performance analysis of image compression using wavelets,” IEEE Trans. Ind. Electron., vol. 48, no. 3, Jun. 2001 pp. 682–695.
[14] 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.
[15] J. Tsotsos, “Analyzing vision at the complexity level,” Behav. Brain. Sci., vol. 13, no. 3, Mar. 1990, pp. 423–445.
[16] A. Adams, The Print. ser. The Ansel Adams Photography series. New York, NY, USA: Little, Brown and Company, 1983.
[17] LAGENDIJK, R. L., BIEMOND, J., AND BOEKEE, D. E. 1988. Regularized iterative image restoration with ringing reduction. IEEE Trans. Acoustics, Speech, and Signal Proc., Speech, Signal Proc. 36, 12, 1874–1888.
[18] K. N. NORDSTROM, 1989. Biased anisotropic diffusion — a unified regularization and diffusion approach to edge detection. Tech. Rep. UCB/CSD-89-514, EECS Department, University of California, Berkeley.
[19] A. LEVIN, D. LISCHINSKI, AND Y. WEISS. 2004. Colorization using optimization. ACM Trans. Graph. 23, 3 (August), 689– 694.
[20] D. LISCHINSKI, Z. FARBMAN, M. UYTTENDAELE, AND R. SZELISKI, 2006. Interactive local adjustment of tonal values. ACM Trans. Graph. 25, 3, 646–653.
[21] P. BURT, AND E. H. ADELSON, 1983. The Laplacian pyramid as a compact image code. IEEE Trans. Comm. 31, 532–540.
[22] J. TUMBLIN, AND G. TURK, 1999. LCIS: A boundary hierarchy for detail-preserving contrast reduction. In Proc. ACM SIGGRAPH 99, A. Rockwood, Ed., ACM, 83–90.
[23] REINHARD, E., STARK, M., SHIRLEY, P., AND FERWERDA, J. 2002, Photographic tone reproduction for digital images. ACM Trans. Graph. 21, 3, 267–276.
[24] H. WINNEM¨OLLER, S. C. OLSEN, AND B. GOOCH, 2006, Realtime video abstraction. ACM Trans. Graph. 25, 1221– 1226.
[25] J. CHEN, S. PARIS, AND F. DURAND, 2007. Real-time edge-aware image processing with the bilateral grid. ACM Trans. Graph. 26, 3, Article 103.