Adaptive solution of temporal scalable decoding process with frame rate conversion method for surveillance video

This paper proposes an adaptive solution of temporal scalable decoding process with frame rate conversion method for surveillance video. It realizes the adaptive skipping scheme in the temporal scalable decoding process based on the content of the pictures. By analyzing the relationship between motion vector energy and the video quality loss of the same frame in probability, chooses the suitable form of the motion vector value to qualify the video quality loss which is caused by the skipping process in a frame. And uses a selecting algorithm based on the energy accumulation principle to realize the adaptive frame skipping. By using this frame rate-down conversion algorithm, the PSNR is improved about 0.2-1.4 dB (compared with the certain frame skipping scheme) in different skipping cases. And the loss of the decoding time reduction is less than 5% in the worst case, but in the most of the cases it is only 0 ~ 2%.