SVM based approach for complexity control of HEVC intra coding

The High Efficiency Video Coding (HEVC) is adopted by various video applications in recent years. Because of its high computational demand, controlling the complexity of HEVC is of paramount importance to appeal to the varying requirements in many applications, including power-constrained video coding, video streaming, and cloud gaming. Most of the existing complexity control methods are only capable of considering a subset of the decision space, which leads to low coding efficiency. While the efficiency of machine learning methods such as Support Vector Machines (SVM) can be employed for higher precision decision making, the current SVM-based techniques for HEVC provide a fixed decision boundary which results in different coding complexities for different video content. Although this might be suitable for complexity reduction, it is not acceptable for complexity control. This paper proposes an adjustable classification approach for Coding Unit (CU) partitioning, which addresses the mentioned problems of complexity control. Firstly, a novel set of features for fast CU partitioning is designed using image processing techniques. Then, a flexible classification method based on SVM is proposed to model the CU partitioning problem. This approach allows adjusting the performance-complexity trade-off, even after the training phase. Using this model, and a novel adaptive thresholding technique, an algorithm is presented to deliver video encoding within the target coding complexity, while maximizing the coding efficiency. Experimental results justify the superiority of this method over the state-of-the-art methods, with target complexities ranging from 20% to 100%.acceptedVersionPeer reviewe

MIMO無線伝送に適したスケーラブルビデオコーディングに関する研究

Because of the COVID-19 pandemic, a new normal has taken over. It affects the higher demand for using video traffic. H.264/SVC is the video compression standard with several advantages compared with the previous standard, such as a smaller storage space and scalability of video quality depending on network quality. The H.264/SVC bitstream includes one base layer (BL), the most important layer, and one or more enhancement layers (EL) which can be leveraged to optimize the video scalability depending on the network condition and user preferences. The method of transmission is powerful as the video coding method. The transmission of the good video quality will not be effective without a suitable transmission method. In this thesis, we study and research the H.264 scalable video coding transmission with IEEE 802.11ac standard MIMO wireless transmission. We focus on the suitable transmission method for H.264/SVC in a different environment. We divide the research focusing on two issues: 1. With the difference channel environment: The suitable H.264/SVC transmission technique in IEEE 802.11ac with the specific quantization parameter of video encoding was proposed. This aim is to compare three techniques in IEEE 802.11ac: STBC, SISO, and MIMO. In this focus, only the accuracy of the video was considered to measure the efficiency of the transmission technique. This part proposed to utilize STBC to improve the quality of H.264/SVC video transmission. We have shown the performance of H.264/SVC video transmission with three multiple antenna techniques. The results show that STBC is the best technique for H.264/SVC transmission under a low-quality channel environment. The best result shows that STBC in channel model D can improve the PSNR by 67 percent and 76 percent compared with SISO and MIMO, respectively, at low SNR of 20 dB. Due to STBC transmitting multiple copies of data, it can increase data reliability. We proved that STBC is the most suitable multiple antenna technique to improve the quality and realizability of video transmission in both PSNR and bit error rate (BER). 2. With the different transmission distance: H.264/SVC video transmission on MIMO with RSSI feedback was proposed. This aim to proposes the allocation of packetization in the transmission packet and the compromising of quantization parameter encoding both vary on the channel efficiency. This part proposed a MIMO transmission system for H.264 scalable video coding that does not require full CSI feedback. Instead of the CSI feedback, we have used the RSSI and table of encoding rules obtained via link simulation in MATLAB. The encoding rule takes the form of the encoding ratio between the base and enhancement layer, which was done by adjusting the quantization parameter. This proposed system has been shown to improve the PSNR by at least 16 dB and increase the effective distance of 6 meters above compared with the conventional method.九州工業大学博士学位論文 学位記番号：情工博甲第372号 学位授与年月日：令和4年12月27日1 Introduction|2 Video Transmission System Overview|3 H.264/SVC Video Transmission by IEEE 802.11ac Techniques|4 H.264/SVC Video Transmission on MIMO with RSSI Feedback|5 Conclusion and Future Work九州工業大学令和4年