Abstract
The latest video coding standard high efficiency video coding (HEVC) has made a significant progress in compression efficiency than previous standard H.264/advanced video coding (AVC) while it has led to a tremendous increase in encoding computations. Recently, a Bayesian model based transform unit (TU) depth decision approach has been designed to accelerate TU depth decision, which requires numerous variance computations. In this work, a novel relevant feature based Bayesian model is proposed for fast TU depth decision. Experimental results demonstrate that the best performance is achieved while the depths of upper TU, left TU and co-located TU are all taken into considerations. Moreover, as compared with previous research, the proposed algorithm reduces much more encoding computations while keeping the video quality and compression efficiency more or less intact.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
