Enhancing Rate Control in Video Coding with a Joint Machine Learning and Game Theory Approach
Business application/Technology/ 11 Jan 2023 BubuPartners Analysis team
Quality vs Quantity in video encoding models
The rate control in video encoding determines the bit allocation for each frame during video compression. To achieve coding efficiency, most encoding schemes use the Rate-Distortion (R-D) model, which trades off quality gains against storage requirements. However, accurate modeling of R-D relationships for Coding Tree Units (CTUs) is essential. Therefore, a new technology proposes a joint advanced machine learning and game theory modeling framework to optimize the bit allocation at the CTU level in High Efficiency Video Coding (HEVC). This approach enhances the rate control performance, including bit rate accuracy, R-D performances, quality smoothness, and buffer control results. As a result, this technology can improve video encoding and decoding performance, leading to better visual experiences for users.
The proposed technology uses a Support Vector Machine (SVM) multi-classification scheme for machine learning and a multiple R-D models based cooperative bargaining game utilizing a Nash Bargaining Solution (NBS) for game theory modeling. These approaches improve the R-D model prediction accuracy for inter-frame CTUs and efficiently distribute the coding bits or communication bandwidth to different CTUs in each frame. Experiments show that this technology outperforms other state-of-the-art one-pass rate control methods.
CTU pave a smoother pathway
The technology’s benefits include more efficient CTU level bit allocation optimization, which leads to better video coding performance, and more efficient compression of large amounts of video data, significantly reducing storage and communication workload and requirements. This technology has potential applications in various industries and fields, including entertainment, communication, and security. It can be used for real-time video streaming applications, such as cable TV programs, video-on-demand services, live TV, and videos over the internet. Additionally, it can be used for real-time video chat and conference on computers or portable devices, personal video cameras, security surveillance systems, medical imaging, and autonomous driving.
