1
PhD Student, Department of Electrical Engineering, Shahid Bahonar University of Kerman
2
Department of Electrical Engineering, Shahid Bahonar University of Kerman
Abstract
This paper proposes a 3-D non-local means (NLMs) method for the application of video inpainting. To do this, first it assigns to the target pixels a priority and then restores them. The priority assignment of the target pixels is done based on structure and texture information of their neighbors’ pixels. To determine the type of each patch, which can be either texture or structure, the entropy criterion is used. The proposed method, to estimate damaged pixels, uses several non-local patches instead of the best matched patch. The subjective and objective experiments confirm the superiority of proposed method in the application of video inpainting and removing moving objects from the video in comparison with state-of-the-art methods.
Sheykhalishahi, F., Saryazdi, S., & Nezamabadipour, H. (2018). A 3-D patches mean method for removing moving objects and video inpainting. Journal of Machine Vision and Image Processing, 5(1), 113-128.
MLA
Fatemeh Sheykhalishahi; Saeid Saryazdi; Hossein Nezamabadipour. "A 3-D patches mean method for removing moving objects and video inpainting". Journal of Machine Vision and Image Processing, 5, 1, 2018, 113-128.
HARVARD
Sheykhalishahi, F., Saryazdi, S., Nezamabadipour, H. (2018). 'A 3-D patches mean method for removing moving objects and video inpainting', Journal of Machine Vision and Image Processing, 5(1), pp. 113-128.
VANCOUVER
Sheykhalishahi, F., Saryazdi, S., Nezamabadipour, H. A 3-D patches mean method for removing moving objects and video inpainting. Journal of Machine Vision and Image Processing, 2018; 5(1): 113-128.
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