The H.264 advanced video coding (H.264/AVC) standard provides several advanced features such as improved coding efficiency and error robustness for video storage and transmission. In order to improve the coding performance of H.264/AVC, coding control parameters such as group-of-pictures (GOP) sizes should be adaptively adjusted according to different video content variations (VCVs), which can be extracted from temporal deviation between two consecutive frames. The authors present a simple VCV estimation to design adaptive GOP detection (AGD) and scene change detection (SCD) methods by using the obtained motion information, where the motion vectors and the sum of absolute transformed differences as VCV features are effectively used to design the AGD and SCD algorithms, respectively. In order to avoid unnecessary computation, the above VCV features are obtained only in the 4×4 inter-frame prediction mode. Simulation results show that the proposed AGD with SCD methods can increase the peak signal-to-noise ratio by 0.62dB on average over the H.264/AVC operated with a fixed GOP size. Besides, the proposed SCD method can reach a scene change detection rate of 98.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering