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An Improved HDR Technique by Classification Method

by Deepali Agarwal, Shilky Shrivastava, Anand Singh Bisen
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 19
Year of Publication: 2015
Authors: Deepali Agarwal, Shilky Shrivastava, Anand Singh Bisen
10.5120/21174-4087

Deepali Agarwal, Shilky Shrivastava, Anand Singh Bisen . An Improved HDR Technique by Classification Method. International Journal of Computer Applications. 119, 19 ( June 2015), 9-15. DOI=10.5120/21174-4087

@article{ 10.5120/21174-4087,
author = { Deepali Agarwal, Shilky Shrivastava, Anand Singh Bisen },
title = { An Improved HDR Technique by Classification Method },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 19 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number19/21174-4087/ },
doi = { 10.5120/21174-4087 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:28.005760+05:30
%A Deepali Agarwal
%A Shilky Shrivastava
%A Anand Singh Bisen
%T An Improved HDR Technique by Classification Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 19
%P 9-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Now a day, HDR image is mostly used in applications of wide range such as next generation broadcast, digital cinema and digital photography, because of its high quality and its good expression ability. In our work we have improved an HDR (High Dimensional image) and changed it into multiple improved Low Dynamic Range (LDR) images. We further used multiple copies of the same image and classified differently as per new Low Dynamic Range. Hence we obtain many new exponentially improved images. These images can be further improved by further LDR technique. Finally, we combine all these images and obtain a final image. This final image will be better as compared to the original image. Hence we have an image which in itself will be improved version of the given image.

References
  1. GORTLER, S. J. ,GRZESZCZUK, R. , SZELISKI, R. , AND COHEN, M. F. The Lumigraph. In SIGGRAPH '96 (1996),pp. 43–54.
  2. LEVOY, M. , AND HANRAHAN, P. Light field rendering. In SIGGRAPH '96 (1996), pp. 31–42.
  3. SZELISKI, R. Image mosaicing for tele-reality applications. In IEEE Computer Graphics and Applications (1996).
  4. WARD, G. J. Measuring and modeling anisotropic reflection. In SIGGRAPH '92 (July 1992), pp. 265–272.
  5. TUMBLIN, J. , AND RUSHMEIER, H. Tone reproduction for realistic images. IEEE Computer Graphics and Applications13, 6 (1993), 42–48.
  6. SCHLICK, C. Quantization techniques for visualization of high dynamic range pictures. In Fifth Euro graphics Workshop on Rendering (Darmstadt, Germany) (June 1994), pp. 7–18.
  7. E. Reinhard, G. Ward, S. Pattanaik, and P. Debevec. High Dynamic Range Imaging: Acquisition, Display and Image-Based Lighting. Morgan Kaufmann Publishers, 2005.
  8. S. Nayar and T. Mitsunaga. High Dynamic Range Imaging: Spatially Varying Pixel Exposures. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR),volume 1, pages 472–479, Jun 2000.
  9. S. Mann and R. W. Picard . On being un digital with digital cameras: extending dynamic range by combining exposed pictures. In Proc. of IS & T 48th annual conference, pages 422–428, 1995.
  10. P. Debevec and J. Malik . Recovering high dynamic range radiance maps from photographs . In SIGGRAPH, 1997.
  11. T. Mitsunaga and S. K. Nayar. Radio metric self calibration. In CVPR, 1999.
  12. G. Ward, E. Reinhard, S. Pattanaik, and P. Debevec, High dynamic range Imaging: acquisition, display, and image-based lighting, Morgan Kaufmann Publisher, 2005.
  13. Y. Bandoh, G. Qiu, M. Okuda, S. Daly, T. Aach, and O. Au, "Recent advances in high dynamic range imaging technology," IEEE Conf. Int. Conf. Image Processing, pp. 3125-3128, 2010.
  14. P. Debevec and J. Malik, "Recovering high dynamic range radiance maps from photographs," Proc. ACM SIGGRAPH, pp. 369-378, August 1997.
  15. E. Land, "The retinex theory of color vision," Scientific American, vol. 237, pp. 108-128, December 1977.
  16. Reinhard, E. , Ward, G. , Pattanaik, S. , Debevec, P. : High dynamic range imaging: Acquisition, display and image-based lighting. Morgan Kaufmann, San Francisco(2005)
  17. Jacobs, K. , Loscos, C. , Ward, G. : Automatic high-dynamic range image generation for dynamic scenes. IEEE Computer Graphics and Applications 28, 84–93 (2008)
  18. LAVEAU, S. , AND FAUGERAS, O. 3-D scene representationas a collection of images. In Proceedings of 12th International Conference on Pattern Recognition (1994), vol. 1, pp. 689–691
  19. MCMILLAN, L. , AND BISHOP, G. Plenoptic Modeling: An image-based rendering system. In SIGGRAPH '95 (1995).
  20. CHEN, E. QuickTime VR - an image-based approach to virtual environment navigation. In SIGGRAPH '95 (1995).
  21. DEBEVEC, P. E. , TAYLOR, C. J. , AND MALIK, J. Modeling and rendering architecture from photographs: A hybrid geometry- and image-based approach. In SIGGRAPH '96(August 1996), pp. 11–20.
  22. S. Lin, J. Gu, S. Yamazaki, and H. -Y. Shum. Radio metric calibration from a single image. In IEEE CVPR, 2004.
  23. M. Granados, B. Ajdin, M. Wand, C. Theobalt, H. P. Seidel, and H. P. A. Lensch. Optimalhdr reconstruction with linear digital cameras. In IEEE CVPR, 2010.
  24. R. Fattal, D. Lischinski, and M. Werman. Gradient domain high dynamic range compression. In SIGGRAPH, pages249–256, San Antonio, Texas, 2002.
  25. J. F. Blinn. Compositing, part 1: Theory. IEEE Computer Graphics & Applications, 14(5):83–87, 1994.
  26. R. Brinkmann. The Art and Science of Digital Compositing. Morgan Kaufmann Publishers, 1999.
  27. T. Porter and T. Duff. Compositing digital images. InSIGGRAPH, pages 253–259, 1984.
  28. R. Szeliski. Image alignment and stitching: A tutorial. Foundations and Trends in Computer Graphics and Vision,2(1), 2008.
  29. S. Raman and S. Chaudhuri. A matte-less, variational approach to automatic scene compositing. In ICCV, 2007.
  30. S. Raman and S. Chaudhuri. Bilateral filter based compositing for variable exposure photography. In EUROGRAPHICS Short Papers, 2009.
  31. A. Agarwala, M. Dontcheva, M. Agrawala, S. Drucker,A. Colburn, B. Curless, D. Salesin, and M. Cohen. Interactive digital photomontage. In SIGGRAPH, 2004.
  32. A. Goshtasby. Fusion of multi-exposure images. Image and Vision Computing, 23:611–618, 2005.
  33. T. Mertens, J. Kautz, and F. V. Reeth. Exposure fusion: A simple and practical alternative to high dynamic range photography. Computer Graphics Forum, 28(1):161–171,2009.
  34. K. Jacobs, C. Loscos, and G. Ward. Automatic high-dynamic range image generation for dynamic scenes. IEEE Computer Graphics and Applications, 28(2):84–93, 2008.
  35. O. Gallo, N. Gelfand, W. Chen, M. Tico, and K. Pulli. Artifact-free high dynamic range imaging. In ICCP, 2009.
  36. M. Uyttendaele, A. Eden, and R. Szeliski . Eliminating ghosting and exposure artifacts in image mosaics. In IEEECVPR, 2001.
  37. W. Zhang and W. -K. Cham. Gradient-directed composition of multi-exposure images. In CVPR, 2010.
  38. C. Rother, V. Kolmogorov, and A. Blake. Grabcut: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. , 23(3):309–314, 2004.
  39. J. Shi and J. Malik . Normalized cuts and image segmentation. IEEE Trans on PAMI, 22(8):888–905, 2000.
  40. E. Borenstein and S. Ullman. Learning to segment. In ECCV,2004.
  41. X. Ren and J. Malik . Learning a classification model for segmentation. In IEEE ICCV, 2003.
  42. A. Vedaldi and S. Soatto. Quick shift and kernel methods for mode seeking. In ECCV, 2008.
  43. D. Hoiem, A. A. Efros, and M. Hebert. Automatic photopop-up. ACM Trans. Graph. ,24(3):577–584, 2005
  44. Simon Silk , Jochen Lang "High dynamic range image deghosting by fast approximate background modelling" Computers & Graphics 36 (2012) 1060–1071.
  45. Abhilash Srikantha ,De sire Sidibe" Ghost detection and removal for high dynamic range images: Recent advances" Signal Processing: Image Communication 27 (2012)650–662.
  46. J. Vis. Commun. Image "HTRI: High time range imaging" R. 24 (2013).
Index Terms

Computer Science
Information Sciences

Keywords

High dynamic range imaging HDR Histogram stretching Denoising.

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