Video logo removal using iterative subsequent matching

Video inpainting methods has a large number of applications and some of these algorithms are specialized for specific applications such as logo removal. There are only a few general video inpainting algorithms most of which are very time-consuming. This problem makes these algorithms unsuitable for fast video inpainting. In this paper, a fast simple logo removal algorithm has been proposed which uses frames of each video shot for logo removal and removes logo from video after a few iterations. A more accurate non-casual version of our algorithm is also proposed which uses both the information of previous and next frames. The quality of the inpainted video is also comparable with well-known video inpainting algorithms.

[1]  Sung Yong Shin,et al.  On pixel-based texture synthesis by non-parametric sampling , 2006, Comput. Graph..

[2]  Patrick Pérez,et al.  Region filling and object removal by exemplar-based image inpainting , 2004, IEEE Transactions on Image Processing.

[3]  Wei-Han Chang,et al.  Broadcast Video Logo Detection and Removing , 2008, 2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[4]  Eli Shechtman,et al.  Space-Time Completion of Video , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Stefano Soatto,et al.  Dynamic Textures , 2003, International Journal of Computer Vision.

[6]  Brendan J. Frey,et al.  Video Epitomes , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[7]  Tai-Pang Wu,et al.  Video repairing under variable illumination using cyclic motions , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Mukesh A. Zaveri,et al.  Tracking based depth-guided video inpainting , 2013, 2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG).

[9]  Yong-Sheng Chen,et al.  Virtual Contour Guided Video Object Inpainting Using Posture Mapping and Retrieval , 2011, IEEE Transactions on Multimedia.

[10]  Richard Szeliski,et al.  Video textures , 2000, SIGGRAPH.

[11]  Guillermo Sapiro,et al.  Video Inpainting Under Constrained Camera Motion , 2007, IEEE Transactions on Image Processing.

[12]  Nizar Bouguila,et al.  Video Completion Using Bandlet Transform , 2012, IEEE Transactions on Multimedia.

[13]  Guillermo Sapiro,et al.  Navier-stokes, fluid dynamics, and image and video inpainting , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[14]  A. Chambolle Practical, Unified, Motion and Missing Data Treatment in Degraded Video , 2004, Journal of Mathematical Imaging and Vision.

[15]  Changsheng Xu,et al.  Automatic TV Logo Detection, Tracking and Removal in Broadcast Video , 2007, MMM.

[16]  Seth Teller,et al.  Video matching , 2004, SIGGRAPH 2004.

[17]  Hideo Saito,et al.  A Novel Inpainting-Based Layered Depth Video for 3DTV , 2011, IEEE Transactions on Broadcasting.