By Sreya Chakraborty Under guidance of Dr K R Rao April 28 2011 Smooth streaming is a challenge in areas where bandwidth is low or limited Modern video transmission and storage are based on RTP IP for real time services Most RTP IP access networks are typically characterized by a wide range of connection qualities and receiving devices The varying connection quality is due to adaptive resource sharing mechanisms of these networks Implications of video traffic smoothing on the numbers of statistically multiplexed H 264SVC H 264 AVC and MPEG 4 part 2 streams 2 Traditional digital video transmission and storage systems are based on H 222 0 H 320 7 International video coding standards H 262 H 263 and MPEG 4 1 2 Simulcast provides similar functionalities as a scalable bit stream Effectiveness of two elementary techniques for mitigating high traffic variability Buffered multiplexing Identify the multiplexer buffer sizes required to support maximum number of streams Video traffic smoothing From the wide spectrum of video traffic smoothing techniques two approaches are Optimal Smoothing minimizes the traffic variability Computational complexity of O M M is the number of video frames Basic Smoothing averages the sizes of a prescribed number of video frames Computationally simple O 1 Fig 1 Basic compression system 10 Fig 2 Typical coding system 10 Fig 3 Block diagram of H 264 14 Fig 4 Luma prediction intra prediction modes in H 264 15 a b Fig 5 Macroblock portioning in H 264 for inter prediction a L R 16x16 8x16 16x8 8x8 blocks b L R 8x8 4x8 8x4 4x4 blocks 15 JM Software 12 This software is a product of Joint Video Team JVT of ISO IEC MPEG and ITU T VCEG The latest version of JM Software is 17 2 It supports both planar and interleaved packed raw image data viz yuv rgb The input file is a configuration file text file and some of the parameters passed in that file are Input file Number of frames to be encoded Frame rate Output frame width and Height Profile level selection GOP size Bit rate control JSVM software 13 This software is a product of Joint Video Team JVT of ISO IEC MPEG and ITU T VCEG The input file is a configuration file text file and some of the parameters passed in that file are Input file Number of frames to be encoded Frame rate Output frame width and Height Profile level selection GOP size Bit rate control JM 17 2 Performance Analysis JM Performance in Baseline Profile Video Sequence akiyo qcif Number of frames encoded 25 GOP IBPBPBPBPB Quantization parameter 25 30 35 40 Number of reference frames 3 Video Sequences Used Baseline File Size 3713 KB QCIF format 176 x 144 YUV 4 2 0 Fig 6 PSNR vs QP for Baseline profile of akiyo qcif Fig 7 Encoding time vs QP for baseline profile of akiyo qcif Scalable Video Coding SVC will be an extension of the H 264 MPEG 4 Advanced Video Coding AVC standard Starting point of SVC extension was designed and proposed by Fraunhofer Institute HHI Standardization of SVC extension is still under way To serve different needs of different users with different displays connected through different network links by using a single bit stream i e a single coded version of the video content Spatial scalability Choose appropriate resolution Temporal scalability Choose convenient frame rate Quality scalability Choose suitable data rate by removing parts of the bit stream Fig 8 B frame prediction structures 8 Hierarchical B frame is used For the H 264 SVC encodings GoP structure IBBBBBBBBBBBBBBB 16 frames 15 B frames per I frame denoted by G 16 B15 Statistical video traffic analysis demonstrates that these encoding parameters settings and GoP structures result overall in a very good rate distortion efficiencies for the respective encoders The SVC extension is built on H 264 MPEG 4 AVC and re uses most of its innovative components As a distinctive feature SVC generates an H 264 MPEG 4 AVC compliant i e backwardscompatible base layer and one or several enhancement layer s The base layer bit stream corresponds to a minimum quality frame rate and resolution e g QCIF video and the enhancement layer bit streams represent the same video at gradually increased quality and or increased resolution e g CIF and or increased frame rate Fig 9 Block diagram of SVC 1 Base layer Upper layer Fig 10 SNR Scalable Fig 11 Decoding process for SNR scalability Ease of adaptation to different terminal capabilities Resource conserving transmission storage and display of video e g in surveillance applications Higher transmission robustness if combined with unequal error protection Ease of Multicast Streaming through heterogeneous networks Incorporates multiple streams in a single stream Customized Can send a single video stream to multiple heterogenous clients Bandwidth and storage space is saved The base video stream layer of lower quality can be stored separately instead of storing all the layers This might be useful for video surveillance H 264 SVC can give a decent manageable picture quality even at 20 40 packet loss in the network while the maximum tolerable packet loss for H 264 AVC might be around 1 5 H 264 SVC 1 video encoding is expected to be widely adopted for wired and wireless networks video transport due to their compression efficiency SVC enables the transmission and decoding of partial bit streams to provide video services with lower temporal or spatial resolutions JSVM Performance Analysis 11 JSVM Performance in Baseline Profile Video Sequence Die Hard Number of frames encoded 30 GOP G16B15 Quantization parameter 25 30 35 40 Fig 12 Video sequence Die Hard 11 Trace preview for the video sequence Die Hard 11 Fig 13 Peak Mean of size vs Average quality PSNR Y for Die Hard 11 Fig 14 Average quality PSNR Y vs Average bit rate for Die Hard 11 Fig 15 Video sequence Citizen Kane 11 Fig 16 Peak Mean of size vs Average quality PSNR Y for Citizen Kane 11 Fig 17 Average quality PSNR Y vs Average bit rate for Citizen Kane 11 In comparison to the scalable profiles of prior video coding standards the H 264 AVC extension for scalable video coding SVC provides various tools for reducing the loss in coding efficiency relative to single layer coding The most important differences are 1 The possibility to employ hierarchical prediction structures for providing temporal scalability with several layers while improving the coding efficiency and increasing the effectiveness of quality and spatial scalable coding 2 New methods for inter layer prediction of motion and residual improving the
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