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Various Obstruction Removal Techniques from a Sequence of Images

Miss Ashwini Gat, Mr. Uday Nuli, Mr. Sandip Murchite, ,
Affiliations
Computer Science & Engineering, TEI’s DKTE, Ichakaranji, 416115/416115, India
:10.22362/ijcert/2017/v4/i3/xxxx [UNDER PROCESS]


Abstract
Reflection or obstruction from images is a major reason for quality degradation of images in image processing. Camera Flash is frequently used to capture a good photograph of a scene under low light conditions. However, flash images have many problems: The flash can often be blinding and too strong, leading to blown out images. This report presents separate algorithms described in the literature that attempts to remove obstructions computationally. The strengths and weaknesses of each algorithm outlined.


Citation
Ashwini Gat et.al, “Various Obstruction Removal Techniques from a Sequence of Images”, International Journal Of Computer Engineering In Research Trends, 4(3):86-88, March-2017.


Keywords : flash, reflection removal, obstruction, SPBSM, SID, GPSR.

References
[1]	K. Gai, Z. Shi, and C. Zhang. Blind separation of superimposed moving images using image statistics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(1):19–32, Jan 2012.

[2]	X. Guo, X. Cao, and Y. Ma. Robust separation of reflection from multiple images. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, pages 2195–2202, June 2014.

[3]	Levin, A. Zomet, and Y.Weiss. Separating reflections from a single image using local features. In Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, Volume 1, pages I–306–I–313 Vol.1, June 2004

[4]	Y. Shih, D. Krishnan, F. Durand, and W. Freeman. Reflection removal using ghosting cues. In Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on, pages 3193– 3201, June 2015.

[5]	S. N. Sinha, J. Kopf, M. Goesele, D. Scharstein, and R. Szeliski. Image-based rendering for scenes with reflections. In ACM Trans. Graph. (August 2012). ACM SIGGRAPH, August 2012.

[6]	A. K. Jain, “Fundamentals of Digital Image Processing” Prentice-Hall, 1986, p 384.

[7]	Amit Agrawal Ramesh Raskar Shree K. Nayar† Yuanzhen Li Mitsubishi “Removing Photography Artifacts using Gradient Projection and Flash-Exposure Sampling” Electric Research Labs (MERL), Cambridge, MA_ †Columbia University

[8]	Li Michael S. Brown “Exploiting Reflection Change for Automatic Reflection Removal” Yu School of Computing, National University of Singapore liyu@nus.edu.sg | brown@comp.nus.edu.sg

[9]	B.himabindu (Asst. professor, Department of E.C.E, Chalapathi Institute of Technology, Guntur, A.P, India). “Removal of Shadows and Reflections in the Images By Using Cross-Projection Tensors” IOSR Journal of Engineering (IOSRJEN) ISSN: 2250-3021 Volume 2, Issue 8 (August 2012), PP 34-40 www.iosrjen.org www.iosrjen.org 34|Page 

[10]	 Mário A. T. Figueiredo, Senior Member IEEE, Robert D. Nowak, Senior Member, IEEE, and Stephen J. Wright “Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems” IEEE journal of selected topics in signal processing, vol. 1, no. 4, december 2007.
[11]	A. Levin, A. Zomet, and Y. Weiss. “Separating reflections from a single image using local features”. In CVPR, 2004. [7]Song,Bo; Gong,shenwen; Ren,chunjian “Removing artifacts using gradient projection from a single image”. MIPPR 2011: Pattern Recognition and Computer Vision. Edited by Roberts, Jonathan; Ma, Jie. Proceedings of the SPIE, Volume 8004, article id. 80041C, 6 pp. (2011). (SPIE homepage). 


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DOI:10.22362/ijcert