CFP last date
22 April 2024
Reseach Article

High Dynamic Range Image Analysis through Various Tone Mapping Techniques

by Manoj Kumar Patle, Bharti Chourasia, Yashwant Kurmi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 153 - Number 11
Year of Publication: 2016
Authors: Manoj Kumar Patle, Bharti Chourasia, Yashwant Kurmi
10.5120/ijca2016912195

Manoj Kumar Patle, Bharti Chourasia, Yashwant Kurmi . High Dynamic Range Image Analysis through Various Tone Mapping Techniques. International Journal of Computer Applications. 153, 11 ( Nov 2016), 14-17. DOI=10.5120/ijca2016912195

@article{ 10.5120/ijca2016912195,
author = { Manoj Kumar Patle, Bharti Chourasia, Yashwant Kurmi },
title = { High Dynamic Range Image Analysis through Various Tone Mapping Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 153 },
number = { 11 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 14-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume153/number11/26447-2016912195/ },
doi = { 10.5120/ijca2016912195 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:58:51.698178+05:30
%A Manoj Kumar Patle
%A Bharti Chourasia
%A Yashwant Kurmi
%T High Dynamic Range Image Analysis through Various Tone Mapping Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 153
%N 11
%P 14-17
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The image quality is improved drastically with the increase of the technology. The conventional display devices may not be suitable for these High dynamic range images. The tone mapping is the process to show the good quality image in the normal LDR display devices. This paper presents a review of the tone mapping algorithms. It provides the methodology on Tone Mapped Image Quality Index (TMIQI) and the Blind Quality Assessment of Tone-Mapped Images (BTMQI). The region is basically expanded and compressed to visualize properly. Thereby the region-enhanced pseudo-exposures are fused into an HDR image. The image quality of BTMQI is comparatively higher than the TMIQI method. The low dynamic range images are suitable to both the conventional and advance display devices.

References
  1. T. Jinno, and M. Okuda, "Multiple exposure fusion for high dynamic range image acquisition," IEEE Trans. on Image Process., vol. 21, no. 1, Jan. 2012, pp. 358-365.
  2. B. Gu, W. Li, M. Zhu, and M. Wang, "Local edge-preserving multiscale decomposition for high dynamic range image tone mapping," IEEE Trans. on Image Process., vol. 22, no. 1, Jan. 2013, pp. 70-79.
  3. H. Yeganeh and Z. Wang, "Objective quality assessment of tone-mapped images," IEEE Trans. on Image Process., vol. 22, no. 2, Feb. 2013, pp. 657-667.
  4. A. Chakrabarti, Y. Xiong, B. Sun, T. Darrell, D. Scharstein, T. Zickler, and K. Saenko, "Modeling radiometric uncertainty for vision with tone-mapped color images," IEEE Trans. on Pattern Analysis And Machine Intelligence, vol. 36, no. 11, Nov. 2014, pp. 2185-2198.
  5. J. Xiao, W. Li, G. Liu, S. L. Shaw, Y. Zhang, "Hierarchical tone mapping based on image colour appearance model," IET Comput. Vis., 2014, vol. 8, no. 4, pp. 358–364.
  6. H. Z. Nafchi, A. Shahkolaei, R. F. Moghaddam, and M. Cheriet, "FSITM: A feature similarity index for tone-mapped images," IEEE Signal Process. Letters, vol. 22, no. 8, Aug. 2015, pp.1026-1029.
  7. T. H. Wang, C. W. Chiu, W. C. Wu, J. W. Wang, C. Lin, C. T. Chiu, and J.J. Liou, "Pseudo-multiple-exposure-based tone fusion with local region adjustment," IEEE Trans. on Multimedia, vol. 17, no. 4, Apr. 2015, pp.470-484.
  8. K. Ma, H. Yeganeh, K. Zeng, and Z. Wang, "High dynamic range image compression by optimizing tone mapped image quality index," IEEE Trans. on Image Process., vol. 24, no. 10, Oct. 2015, pp. 3086-3097.
  9. K. Gu, S. Wang, G. Zhai, S. Ma, X. Yang, W. Lin, W. Zhang, and Wen Gao, "Blind quality assessment of tone-mapped images via analysis of information, naturalness, and structure," IEEE Trans. on Multi., vol. 18, no. 3, Mar. 2016, pp. 432-443.
  10. T. Tan and A. G. Constantinides, "Multi-Slice Image Texture Edge Detection by Local Vector Mapping," IEEE, 1988, pp. 1136-1139.
  11. Y. Kurmi and V. Chaurasia, “An image fusion approach based on adaptive fuzzy logic model with local level processing,” Int. Jour. of Comp. Appl., Aug. 2015, vol. 124, no.1, pp. 39-42.
  12. D. Sharma, Y. Kurmi, and V. Chaurasia, “Formation of super- resolution image: a review,” Int. Jour. of Emerging Tech. and Adv. Engg., Apr. 2014, vol. 4, no. 4, pp. 218-221.
  13. Y. Kurmi and V. Chaurasia, “Performance of haze removal filter for hazy and noisy images,” Int. Jour. of Sci. Engg. and Tech., Apr. 2014, vol. 3 no. 4, pp. 437-439.
  14. S. Tiwari, K. Chauhan, and Y. Kurmi “Shadow detection and compensation in aerial images using MATLAB,” Int. Jour. of Comp. Appl., June 2015, vol. 119, no.20, pp. 5-9.
  15. T. S. Huang, "Coding of two tone images," IEEE Trans. on Commu., Nov. 1977, vol. Com-25, no. 11, pp. 1406-1424.
  16. A. lranli and M. Pedram, "DTM: Dynamic Tone Mapping for Backlight Scaling," Anaheim, California, USA, DAC June 13-17, 2005, pp. 612-617.
  17. C. E. Shannon, “A mathematical theory of communication,” Bell Syst. Tech. J., vol. 27, no. 3, pp. 379–423, Oct. 1948.
  18. W. Xue, L. Zhang, and X.Mou, “Learning without human scores for blind image quality assessment,” in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recog., Jun. 2013, pp. 995–1002.
  19. A. K. Moorthy and A. C. Bovik, “Blind image quality assessment: From scene statistics to perceptual quality,” IEEE Trans. Image Process., vol. 20, no. 12, pp. 3350–3364, Dec. 2011.
  20. M. A. Saad, A. C. Bovik, and C. Charrier, “Blind image quality assessment: A natural scene statistics approach in the DCT domain,” IEEE Trans. Image Process., vol. 21, no. 8, pp. 3339–3352, Aug. 2012.
  21. A. Mittal, A. K. Moorthy, and A. C. Bovik, “No-reference image quality assessment in the spatial domain,” IEEE Trans. Image Process., vol. 21, no. 12, pp. 4695–4708, Dec. 2012.
Index Terms

Computer Science
Information Sciences

Keywords

High dynamic range imaging structural preservation tone mapping perceptual image processing structural similarity