Image inpainting

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object],[object Object]

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object]

IMAGE INPAINTING ,[object Object],[object Object],[object Object],Figure 1: Removing unwanted objects from the Image

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

IMAGE INPAINTING ,[object Object],Figure 2: Selecting target region using our tool.

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Figure 3: Terminologies used in inpainting[2]

IMAGE INPAINTING ,[object Object]

IMAGE INPAINTING ,[object Object],[object Object],[object Object],Figure 4: Input Image to the inpainting module

IMAGE INPAINTING ,[object Object],[object Object],Laplacian Filter Figure 5: Boundary of the target region 1 1 1 1 -8 1 1 1 1

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],(a) (b) (c) (d)

IMAGE INPAINTING ,[object Object],Figure 7: Notation Diagram [2].

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object],Figure 8: Dropping Effect. (a) data term (b) confidence term (c) priority function

IMAGE INPAINTING ,[object Object],[object Object],[object Object]

IMAGE INPAINTING ,[object Object],(a) (b) (c) Figure 9: (a) Input Image (b) Output using our implementation of Crimnisi’s approach. (c) Our Approach.

IMAGE INPAINTING ,[object Object],[object Object],[object Object],[object Object],[object Object],where, m = number of rows in the patch. n = number of columns in the patch. c r = maximum number of continuous green pixels in one row c c = maximum number of continuous green pixels in one column D x and D y are constants.

IMAGE INPAINTING ,[object Object],Figure 10: Comparison with Criminisi’s Approach (a) The input image of size 416 x 316 [2]. (b) The image with island to be removed marked in green color. (c) The output using our implementation of Criminisi’s approach. The time taken was 2 minutes 35 seconds. (d) The output using our algorithm. Time taken was 2 minutes and 5 seconds. (a) (b) (d) (c)

IMAGE INPAINTING ,[object Object],Couldn’t get a clear shot of the scene.

IMAGE INPAINTING ,[object Object],[1] Marcelo Bertalmio et. al., “Image Inpainting”, in International Conference on Computer Graphics and Interactive Techniques, Proceedings of the 27th annual conference on Computer graphics and interactive technique , 2000 (Available: http://portal.acm.org/citation.cfm?id=344972 ) [2] A. Criminisi, P. Perez and K. Toyama, “Region Filling and Object Removal by Exemplar- Based Image Inpainting”, in IEEE Transactions on Image Processing , Vol. 13, No. 9, September 2004 (Availble: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.67.9407&rep=rep1&type=pdf ) [3] Manuel M. Oliveira, Brian Bowen, Richard McKenna and Yu-Sung Chang, “Fast Digital Image Inpainting”, in Proceedings of the International Conference on Visualization, Imaging and Image Processing (VIIP 2001) , Marbella, Spain. September 3-5, 2001 (Available: http://www.inf.ufrgs.br/~oliveira/pubs_files/inpainting.pdf ) [4] Timothy K. Shih et. al., “Video inpainting and implant via diversified temporal continuations, in International Multimedia Conference, Proceedings of the 14th annual ACM international conference on Multimedia , 2006 (Available: http://portal.acm.org/citation.cfm?id=1180678 ) [5] A.C. Kokaram, R.D. Morris, W.J. Fitzgerald, P.J.W. Rayner. “Interpolation of missing data in image sequences”, in IEEE Transactions on Image Processing 11(4) , pp. 1509-1519, 1995. [6] P.Elango and K.Murugesan. “Digital Image Inpainting Using Cellular Neural Network, in Int. J. Open Problems Compt. Math. , Vol. 2, No. 3, pp. 439-450, September 2009 (Available: http://www.emis.de/journals/IJOPCM/Vol/09/IJOPCM%28vol.2.3.8.S.9%29.pdf )

IMAGE INPAINTING ,[object Object],[7] Carola-Bibiane Schonlieb, Andrea Bertozzi, Martin Burger and Lin He. “Image Inpainting Using a Fourth-Order Total Variation Flow”, in SAMPTA’09 , Marseille, France, 2009 (Available: ftp://ftp.math.ucla.edu/pub/camreport/cam09-34.pdf ) [8] Martin Burger, Lin He and Carola-Bibiane Schonlieb. “Cahn-Hilliard Inpainting and a Generalization for Grayvalue Images”, in UCLA CAM report , pp. 08-41, June 2008 (Available: ftp://ftp.math.ucla.edu/pub/camreport/cam08-41.pdf ) [9] M Elad, J. –L Starck, P. Querre and D.L. Donoho. “Simultaneous Cartoon and texture image inpainting using morphological component analysis (MCA)”, Journal on Applied and Computational Harmonic Analysis , August, 2005 (Available: http://irfu.cea.fr/Phocea/file.php?class=std&&file=Doc/Publications/Archives/dapnia-05-292.pdf ) [10] Guillaume Forbin, Bernard Besserer, Jiri Boldys and David Tschumperle. “Temporal Extension to Exemplar-Based Inpainting applied to scratch correction in damaged image sequences”, in Visualization, Imaging and Image Processing (VIIP 2005) , Benidorm : Espange, 2005 (Available: http://prestospace.org/training/images/viip2005.pdf ) [11] R.C. Gonzalez and R.E. Woods, Digital Image Processing , 2 nd ed. Pearson Education, 2002. [12] M.J. Fadili, J. –L. Starck and F. Murtagh. “Inpainting and zooming using Sparse Representations”, The Computer Journal , 2009 (Available: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.100.6938&rep=rep1&type=pdf ) [13] Wen-Huang Cheng, Chun-Wei Hsieh, Sheng-Kai Lin, Chia-Wei Wang and Ja-Ling Wu. “Robust Algorithm for Exemplar-Based Image Inpainting”, in The International Conference on Computer Graphics, Imaging and Vision (CGIV 2005) , 26-29 July 2005, Beijing, China, pp. 64-69.

Image inpainting

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