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Compressed Video Communications Abdul Sadka Copyright © 2002 John Wiley & Sons Ltd ISBNs: 0-470-84312-8 (Hardback); 0-470-84671-2 (Electronic) 3 Flow Control in Compressed Video Communications 3.1 Introduction In multimediacommunications, compressed video streams need to be transmitted over networks that have inconsistent and time-varying bandwidth requirements. To make the best use of available network resources at any time and guarantee a maximum level of perceptual video quality from the end-user’s perspective, a certainflowcontrolmechanismmustbeintroducedintothevideocommunication system(Coteet al., 1998; Wang, 2000).Over-ratingthe outputof avideocoder can cause an undesirable traffic explosion and lead to congested networks. On the other hand, uncontrolled reduction of the output bit rate of a video coder leads to unnecessary quality degradation and inefficient use of available bandwidth re-sources. Flow control techniques must then be employed to regulate and control the output bit rates of video sources in the network to achieve the best trade-off between quality and bandwidth utilisation (Girod, 1993). One of the main challengesof video communicationsis to providea guaranteed qualityofservicewhenthenetworkisswampedwithexcessivedelaysandinforma-tion loss rates (Kurose, 1993). Network congestion could be avoided by using preventiveinstead of reactiveremedies. Congestion avoidancetechniques in video communications must consist of an efficient flow control mechanism that regu-lates the rates of active video sources (Jacobson, 1988). In a bit rate regulation scheme, the video source might sometimes be required to decrease its output flow due to high traffic load across the network. This reduction in bit rate could certainly lead to quality degradation since the quantisation distortion becomes more noticeable at lower bit rates. However, the quality degradation resulting fromacoarserquantisationprocessis farlessdetrimentaltothevideoqualitythan the effect of intolerable time delays and high data loss rates caused by a state of network congestion. Network congestion effects could also be more disastrous in real-time video services where the decoded video quality is much less tolerant to delay and data loss. Therefore, some policy must be adopted to prevent the 76 FLOW CONTROL IN COMPRESSED VIDEO COMMUNICATIONS occurrenceofcongestionor reduceits effectin hightrafficloadconditions.A lot of research efforts have been exerted to establish efficient techniques for resolving congestion. Bolot and Turletti (1994) have developed a feedback control mechan-ismforflowcontrolofvideosourcesoverthemulticastbackbone(Kumar,1996)of the Internet. In this preventive rate control scheme, the rate control of a video encoder is regulated by modifying some encoding parameters, as indicated by somefeedbackmessages sentby networkreceivers.Each receiversendsafeedback message that includes some statistics data such as average packet transit time, averagelossrateformulticasttraffic,averagepacketdelay,etc.Thesendercollates this data and adjusts its output flow accordingly. Another feedback mechanism (Bolot, Turletti and Wakeman, 1994) employs a probing technique to solicit information and estimate the number of receivers in a multicast tree. A number of video scaleability paradigms (Radha et al., 1999; Stuhlmuller, Link and Girod, 1999; Horn and Girod, 1997) have been proposed for Internet streaming applica-tions. Other research efforts produced reactive approaches such as error conceal-ment and video data recovery schemes, which we will elaborate on in the next chapter.In this chapter, we present a variety ofrate control algorithmsthat can be used in compressed video communications today. These algorithms can perform dynamically in accordance with the varying channel conditions. The status of the channel is reported back to the video source by a number of receivers that have special traffic data compilation capabilities. These feedback reports make the video source more network-aware and thus contribute to efficiently adapting the flow control algorithms to the reported channel conditions at any instant of time. 3.2 Bit Rate Variability of Video Coders All the standard video coding algorithms described in the previous chapter produce a variable bit rate per frame for a constant quantisation parameter. To guaranteea constant perceptual quality of the decoded sequence, it is necessaryto keep a constant quantiser value Qp during the encoding process. Alternatively, varying the quantiser value on a frame or MB basis could achieve a constant outputbit rate but at the expense of an undesirablevariation in the decoded video quality.Anewvariablequantiserratecontrolalgorithmhasbeenproposed(Perra, Pinna and Giusto, 2000) to produce a minimal output bit rate for a fixed objective quality. The relationship between the temporal activity and quality of service in video communications is shown in Figure 3.1 for both fixed and variable bit rate encoding. In addition to the constant quality justification of variable rate video, the fluctuation of bit rates is also useful for the dynamic allocation of available bandwidth. As described in Chapter 2, a video source produces a higher output rate with a more active scene or more detailedtexture. The drop in the outputrate of a video source could be exploited to allocate a larger portion of bandwidth to a 3.2 BIT RATE VARIABILITY OF VIDEO CODERS 77 Temporalactivity Time Bit rate Quality (a) Fixed rate (variable quality) Time Quality Bit rate (b) Variable rate (fixed quality) Time Figure 3.1 Relationship between quality and bit rate more active source in the network, thereby ensuring a more efficient bandwidth sharing than for the fixed bandwidth scenario. However, this dynamic bandwidth allocation requires a flow control mechanism which can police and dictate the output traffic of each video source on the network in accordance with the time-varying network conditions and requirements. In general, there are two main reasonswhyablock-transformvideocoderhasthisvariablebitratecharacteristic. A digital video signal incorporates a huge amount of sequence-dependent redundancies in both time and space. The compression efficiency of a video encoder is determined by the amount of redundancy that is detected and sup-pressedfromthevideosequenceinboththespatialandtemporaldomains.Itisthe proportional removal of these spatial and temporal redundancies which make the 78 FLOW CONTROL IN COMPRESSED VIDEO COMMUNICATIONS output bit rate a variable function of time. For instance, an MB in a predicted frame could represent an unchanged picture area between two successive frames. Therefore, this MB remains stationary as compared to the corresponding MB in theprecedingframe. In this case, the block-transformvideoencoderdoes not code the MB for improved coding efficiency but sets a single bit flag (COD\1) indicating to the decoder that this MB has been skipped in the encoding process. The number of uncoded MBs in predicted frames is certainly a function of the temporal correlations in the video content. This number also depends on the temporal similarities criteria used by the encoder as to whether a certain MB in a predicted frame is to be coded or skipped. The variability of the number of coded MBs in predicted frames certainly leads to a variable output bit rate. On the other hand, the spatial correlations between pixels of the same video frame dictate the numberofbitsrequiredtoencodethe64transformcoefficientsofeach8]8block of data. This is in addition to the chosen quantisation parameter that controls the number of zero coefficients and non-zero levels that are fed into the run-length encoder.Obviously,sincethequantisedcoefficients(TCOEFF)ofthevideoblocks result in different levels and zero-run lengths, the run-length encoder produces a different number of VLC words (RUN, LEVEL) per block even when the quan-tisation parameter remains constant throughout the encoding process. Moreover, thetemporalscaleabilityfeatureenabledbymulti-layercoding,suchasinMPEG-4 for instance, contributes towards the variable output bit rate. Different VOP rates, frame skipping, different quantisation parameters per video layer, are all factors that contribute to this highly time-varying output bit rate. The second factor that leads to the bit rate variability in video coding algo-rithms is the presence of Huffman coding. Variable-length coding is used to optimisethecompressionefficiencybyachievingan optimalaveragebit lengthper codeword. As opposed to fixed-length coding, Huffman coding attempts to assign a code to a certain event, such as a run of zeros, based on the likelihood of its occurrence. The more likely the event, the shorter the code and vice versa. For some video parameters defined by the syntax of a video coding algorithm, such as ITU-T H.263 (Refer to Appendix A), specific Huffman tables are defined. These tables are used to guarantee an optimal average number of bits per coded video parameter. However, due to spatial correlations of video data, different areas of a video frame could be coded at different compression ratios, hence with different numberofbits,eveniftheyhappen tohavean equalnumberofMBs and/orpixels. This could be best demonstrated by assigning variable-length codes to the differ-ent runs of zeros and non-zero levels produced by the run-length encoder. Table 3.1 lists the fixed and variable-length video parameters of the H.263 compression algorithm.Althoughthe tableshows more parametersthat arefixed-lengthcoded, the contribution of variable-length parameters to the overall output bit rate is muchhigher than that of fixed-lengthparameters.Therefore, the percentageof the bits correspondingto variable-length parametersis much higher than that of their fixed-length counterparts. This conclusion is better illustrated in Table 3.2 which 3.3 FIXED RATE CODING 79 Table 3.1 Fixed and variable length video parameters in H.263 coding algorithm Layers Picture Group of Blocks Macroblock Block Codes Variable length Bit Suffing Bit Suffing Administrative Motion DCT Coefficients (except Intra DC terms) ESTUF, PSTUF GSTUF MCBPC, MODB, CBPY MVD, MVD2-4, MVDB TCOEFF Fixed length Synchronisation Addressing Quantisation step size Administrative Spare Synchronisation Addressing Administrative Quantisation step size Administrative Quantisation step size DC terms of Intra DCT Coefficients PSC(22), ECS (22) TR (8), TRB (3) PQUANT (5), DBQUANT (2) PTYPE (13), CPM (1), PSBI (2) PEI (1), PSPARE (8) GBSC (17) GN (5) GSBI (2), GFID (2) GQUANT (5) COD (1), CBPB (6) DQUANT (2) INTRADC (8) showsthatmost ofthebits of anH.263stream,forthe Foremansequencecodedat 30kbit/s, are due to the variable-length codes. More precisely, the statistics show that the DCT coefficients (excluding the fixed-length INTRADC codes) and the differentialMV componentscontributeto 75 per cent of the overall output flow of the encoder. 3.3 Fixed Rate Coding Although a variable bit rate is sometimes desirable for dynamic bandwidth allocation,constant bit rate transmissions are useful for fixed bandwidth channels such as PSTN. To achieve fixed rate video transmissions, a buffer between the video encoder and the channel is used to smooth out the bit rate fluctuations. Obviously, buffering the compressed video streams before transmission entails a certain amount of delay, which must be avoided or at least minimised in real-time video services. This buffer could only regulate the output bit rate for short-term variations. In some video sequences, bit rate fluctuations could last for several frames and thus a large buffer would then be required to absorb long-term ... - tailieumienphi.vn