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

• 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.
• 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.
• 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.
• P. C. Hansen, J. G. Nagy, and D. P. O’Leary, Deblurring Images: Matrices, Spectra, and Filtering, vol. 3. Philadelphia, PA, USA:SIAM, 2006.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• S. Zhuo, D. Guo, and T. Sim, “Robust flash deblurring,” in Proc. IEEE Conf. CVPR, Jun. 2010, pp. 2440–2447.
• 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.
• 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.
• R. Matsuoka, T. Yamauchi, T. Baba, and M. Okuda, “Weight optimization for multiple image integration,” in Proc. IEEE ICIP, Sep.2013, pp. 795–799.
• S. Cho and S. Lee, “Fast motion deblurring,” ACM Trans. Graph., vol. 28, no. 5, pp. 145:1–145:8, 2009.
• L. Mai and F. Liu, “Kernel fusion for better image deblurring,” in Proc. IEEE Conf. CVPR, Jun. 2015, pp. 371–380.
• Misaligned Image Integration with Local Linear Model by Tatsuya, Ryo Matsuoka, Keiichiro Shirai and Masahiro Okuda.