Enhancement for face video from omni-directional video camera
Junwen Wu, Mohan Manubhai Trivedi · 2005
In this paper we propose a novel algorithm to enhance the face video from omni-directional video camera. A two-stage strategy is used. First stage is the noise elimination, realized by iterative MAP update. Naive Bayesian criterion is used to model the posterior. The predominant salt and pepper noise introduced by the omni-to-perspective transformation can be removed effectively, while the image details are well preserved. The high frequency component compensation (HFCC) super-resolution algorithm is applied thereafter to remove the blocky effect. Experimental results show that the video quality has a marked improvement.