Content based search mode improvement for B frame in HEVC

Motion Estimation is most important part of almost all video coding standards such as H.262/MPEG-2, H.264/MPEG-4 and High Efficiency Video Coding (H.265/HEVC). The HEVC is latest video compression standard and has incorporated many improvements like bitrate reduction, increased coding efficiency and compression efficiency but at the cost of increased complexity. The complexity of H.265 is increased due to Motion Estimation (ME), as it consumes almost half time of total time. Motion Estimation algorithm used in reference software code is robust and it is independent of motion information of videos. Real world video sequences show a wide range of motion related information which varies from uniform to random. If the motion characteristics of video sequences are taken into account earlier, it is possible to develop a fast motion estimation algorithm for video sequences. The proposed algorithm includes motion vector prediction which uses motion data of neighboring candidates and motion classification using the characteristics of video sequences. Based on the type of motion the algorithm chooses between different search patterns to enhance the matching process. Early termination helps to additional speedup and improves the process. The proposed method is going to be evaluated using different metrics like percentage reduction in coding time, PSNR, Bit Rate and RD graph.