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Restoration of Color Images using Image Integration based on SURF Features

by M. Sirisha, G. Prasanna Kumar, P. S. N. Murthy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 6
Year of Publication: 2017
Authors: M. Sirisha, G. Prasanna Kumar, P. S. N. Murthy
10.5120/ijca2017915419

M. Sirisha, G. Prasanna Kumar, P. S. N. Murthy . Restoration of Color Images using Image Integration based on SURF Features. International Journal of Computer Applications. 174, 6 ( Sep 2017), 31-34. DOI=10.5120/ijca2017915419

@article{ 10.5120/ijca2017915419,
author = { M. Sirisha, G. Prasanna Kumar, P. S. N. Murthy },
title = { Restoration of Color Images using Image Integration based on SURF Features },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2017 },
volume = { 174 },
number = { 6 },
month = { Sep },
year = { 2017 },
issn = { 0975-8887 },
pages = { 31-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number6/28414-2017915419/ },
doi = { 10.5120/ijca2017915419 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:21:27.639994+05:30
%A M. Sirisha
%A G. Prasanna Kumar
%A P. S. N. Murthy
%T Restoration of Color Images using Image Integration based on SURF Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 6
%P 31-34
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A flash and long-exposure image pair captured in a dark environment is blurred and noisy. To remove this blur or noise from the image pair there are so many deblurring techniques existing. In this paper implemented a new technique for Restoration of Color Images is introduced. In previous methods, image integration is performed only for well-aligned images, which is a difficult process. This problem can be solved by transferring the color of the flash image using a small fraction of the corresponding pixels in the long-exposure image. Proposed method integrates the color of the long-exposure image with the detail of the flash image using Speeded-Up Robust Features (SURF). This method does not require perfect alignment between the images than the previous methods. Proposed method generates integrated image which has a high contrast than the previous method which is based on SIFT.

References
  1. A. Buades, B. Coll, and J.-M. Morel, “A review of image denoising algorithms, with a new one,” Multisc. Model. Simul., vol. 4, no.2, pp.490–530, 2005.
  2. A. Buades, B. Coll, and J.-M. Morel, “A non-local algorithm for image denoising,” in Proc. IEEE Conf. CVPR, vol. 2. June. 2005, pp. 60–65.
  3. M. Elad and M. Aharon, “Image denoising via sparse and redundant representations over learned dictionaries,” IEEE Trans. Image Process., vol. 15, no. 12, pp. 3736–3745, Dec. 2006.
  4. P. C. Hansen, J. G. Nagy, and D. P. O’Leary, Deblurring Images: Matrices, Spectra, and Filtering, vol. 3. Philadelphia, PA, USA:SIAM, 2006.
  5. K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3D transform-domain collaborative filtering,” IEEE Trans. Image Process., vol. 16, no. 8, pp. 2080–2095, Aug. 2007.
  6. A. Beck and M. Teboulle, “Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems,” IEEE Trans. Image Process., vol. 18, no. 11, pp. 2419–2434, Nov. 2009.
  7. Q. Shan, J. Jia, and A. Agarwala, “High-quality motion deblurring from a single image,” ACM Trans. Graph., vol. 27, no. 3, pp. 73:1– 73:10, 2008.
  8. S. Ono and I. Yamada, “A convex regularizer for reducing color artifact in color image recovery,” in Proc. IEEE Conf. CVPR, Jun. 2013, pp. 1775–1781.
  9. G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe, and K.Toyama, “Digital photography with flash and no-flash image pairs,” ACM Trans. Graph., vol. 23, no. 3, pp. 664–672, Aug. 2004.
  10. T. Baba, R. Matsuoka, S. Ono, K. Shirai, and M. Okuda, “Flash/no-flash image integration using convex optimization,” in Proc. IEEE ICASSP, May 2014, pp. 1185–1189.
  11. K. He, J. Sun, and X. Tang, “Guided image filtering,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 6, pp. 1397–1409, Jun. 2013.
  12. K. Shirai, M. Ikehara, and M. Okamoto, “Noiseless no-flash photo creation by color transform of flash image,” in Proc. IEEE ICIP, Sep. 2011, pp. 3437–3440.
  13. S. Zhuo, D. Guo, and T. Sim, “Robust flash deblurring,” in Proc. IEEE Conf. CVPR, Jun. 2010, pp. 2440–2447.
  14. H.-J. Seo and P. Milanfar, “Robust flash denoising/deblurring by iterative guided filtering,” EURASIP J. Adv. Sig. Process., vol. 2012(1), no. 3, pp. 1–19, 2012.
  15. R. Matsuoka, T. Baba, M. Okuda, and K. Shirai, “High dynamic range image acquisition using flash image,” in Proc. IEEE ICASSP, May 2013, pp. 1612–1616.
  16. R. Matsuoka, T. Yamauchi, T. Baba, and M. Okuda, “Weight optimization for multiple image integration,” in Proc. IEEE ICIP, Sep.2013, pp. 795–799.
  17. S. Cho and S. Lee, “Fast motion deblurring,” ACM Trans. Graph., vol. 28, no. 5, pp. 145:1–145:8, 2009.
  18. L. Mai and F. Liu, “Kernel fusion for better image deblurring,” in Proc. IEEE Conf. CVPR, Jun. 2015, pp. 371–380.
  19. Misaligned Image Integration with Local Linear Model by Tatsuya, Ryo Matsuoka, Keiichiro Shirai and Masahiro Okuda.
Index Terms

Computer Science
Information Sciences

Keywords

Blur integration SURF aligned images

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