As a state-of-the-art video compression technique, H.264/AVC has been deployed in many surveillance cameras to improve the compression efficiency. However, it induces very high coding complexity, and thus high power consumption. In this paper, a difference detection algorithm is proposed to reduce the computational complexity and power consumption in surveillance video compression by automatically distributing the video data to different modules of the video encoder according to their content similarity features. Without any requirement in changing the encoder hardware, the proposed algorithm provides high adaptability to be integrated into the existing H.264 video encoders. An average of over 82% of overall encoding complexity can be reduced regardless of whether or not the H.264 encoder itself has employed fast algorithms. No loss is observed in both subjective and objective video quality.
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Electrical and Electronic Engineering