Title :
Recursive Video Matting and Denoising
Author :
Prabhu, Sahana M. ; Rajagopalan, A.N.
Author_Institution :
Dept. of Electr. Eng., HTM, Chennai, India
Abstract :
In this paper, we propose a video matting method with simultaneous noise reduction based on the Unscented Kalman filter (UKF). This recursive approach extracts the alpha mattes and denoised foregrounds from noisy videos, in a unified framework. No assumptions are made about the type of motion of the camera or of the foreground object in the video. Moreover, user-specified trimaps are required only once every ten frames. In order to accurately extract information at the borders between the foreground and the background, we include a discontinuity-adaptive Markov random field (MRF) prior. It incorporates spatio-temporal information from the current and previous frame during estimation of the alpha matte as well as the foreground. Results are given on videos with real film-grain noise.
Keywords :
Kalman filters; Markov processes; image denoising; video signal processing; alpha mattes; discontinuity-adaptive Markov random field prior; foreground denoising; recursive video denoising; recursive video matting; simultaneous noise reduction; spatio-temporal information; unscented Kalman filter; user-specified trimaps; Colored noise; Image color analysis; Kalman filters; Mathematical model; Noise reduction; Pixel; Kalman filter; denoising; video matting;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.1099