Reference Picture Synthesis for Video Sequences Captured with a Monocular Moving Camera Interframe prediction plays an important role in video coding by predicting the current frame from previously encoded pictures, called reference pictures. In the case of camera motion, the content of a current frame could be very different from its reference pictures and may consequently lead to a more difficult Motion Compensation (MC). The main idea of this paper is to process the input 2D video sequence in order to estimate the 3D geometry of the scene and then employ this data to virtually synthesize geometrically compensated reference pictures. Since these virtual reference pictures are more similar to the current frame, motion estimation and consequently coding efficiency could be enhanced. The proposed method is tested over six different video sequences and around 11% bitrate reduction is achieved compared to the High Efficiency Video Coding (HEVC) standard.

MotionCompensated Filtering of Reference Picture for Video Coding Noisy video occurs frequently in many visual communication applications, especially in video surveillance and video phone. The noise affects compression a lot by decreasing the accuracy of prediction and increasing the residual. In this paper, we propose a novel interframe filtering method based on motion compensation for reference picture in video coding. It constructs the lowpass temporal filter by modulating the constructed picture with previous reference picture. As a result, it greatly reduces the noise in reference picture, which results in the improvement of compression efficiency. As the replacement of traditional reference picture, this proposed dynamical motion compensation based Synthesized Reference (SR) picture is computation efficient and easy for implementation. It can be applied to any blockbased hybrid coding structure, such as H.264AVC, AVS (Audio Video Coding Standard), MPEG4. Simulation results show that more than 20% bit rate is reduced when applying SR picture to the encoding of typical video surveillance sequences. At the same time, the visual quality is greatly improved.