Study On Rate Control And Parallel Process For H.264/AVC Video Coding

The H.264/AVC encoding standard jointly launched by ITU and MPEG is one ofthe most widely used video encoding standards and it replaces the existing videocompression standard in the real-time applications dominant such as network videoservices.The rate control technology adopted by H.264/AVC can improve the videocompression rate and provide users with good video reconstruction quality, but theyincrease the H.264/AVC computing complexity. So it will take more time-consuming toencode the same video sequence. This is very unfavorable for low-latency real-timevideo applications. In addition, the video encoding is a complicated calculation processand it needs very high processing capability of the computer. Currently, the computecapability of a single processor can’t meet the demand for real-time application in thevideo encoding.It is an effective method to solve the above problems by constructingthe video service system onto the cloud computing platform and parallel encoding thevideo sequences.Based on a systematical summary of relevant works on H.264encoder and cloudcomputing,this dissertation thorough research on the key technologies of codingdistortion and coding speed involved in the video service system.The main worksinclude:1. A noval joint rate-distortion model based on the exponential function is proposed.The model aims to resolve the larger prediction error problem in quadratic model andlinear tracking models which are adopted by H.264/AVC. The analysis shows that thenew joint rate-distortion model can well reflect the relationship between R,QP and C.2. According to the different characteristics of the I-frames and P-frames, theintraframe encoding complexity calculation model and interframe encoding complexityprediction model are proposed,aiming at the high computational complexity of theH.264/AVC encoding mode selection. The intraframe encoding complexity calculationmodel utilizes the geometric gradient as a measure of the complexity and it caneffectively reduce the computation complexity of the encoding to accelerate the intra-frame encoding process. The interframe encoding complexity prediction modeluses the best one of the four forecasting methods to effectively reduce the frameencoding complexity prediction error.3. In order to resolve these problems that quantization parameter calculation is notaccurate and the bit-rate mismatches in fast motion or scene suddenly switch forH.264/AVC video, a intra-only rate control algorithm and a P-frame rate controlalgorithm.are proposed. Introducing the current I-frame encoding complexity to thequantization parameter calculation and the I-frames and P-frames with different bitallocation strategy, the new rate control algorithm compensates H.264/AVC inadequatein the above two aspects. The experiments show that the new rate control algorithm canachieve higher PSNR gain and the buffer filling degree controls more accurately, frameskipping fewer, more precisely predicted frame encoding complexity and the errorsmaller compared to JVT-W042.4. A parallel video encoding architecture based on the Map/Reduce is proposed.Inorder to resolve the problem that resource utilization is unbalanced and large-scale dataprocessing is low efficiency for video service system in the real-time applications withlow latency,this dissertation adopts virtualization technology and task schedulingstrategy in cloud computing according to the the heterogeneous and dynamiccharacteristics of the video encoding.The experiments show the video parallel encodingsystem can effectively improve the speed of video encoding.5. A Load Balance Max-Min(LBMM) task scheduling algorithm under a cloudenvironment based on video encoding frame characteristics and the correspondingencoding complexity computing model.is proposed. The scheduling algorithm considersthe real-time status of the video sub-frame encoding sequence complexity and servernodes to optimize the allocation of video subsequence scheduling. The experimentalresults show LBMM scheduling algorithm can significantly reduce the entire time spanof the video encoding.