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`1868‘
`
`IEEE TRANSACTIONS ON COMMUNICATTONS, VOL. COM-29, NO. 12, DECEMBER $1981
`
`on
`
`Statistical’ Performance Analysis of an Interframe Encoder;
`fdr Broadcast Television Signals
`‘
`T
`TOSHIO KOGA, YUKIHIKO IIJIMA, KAZUMOTO HNUMA, AND TATSUO ISHIGURO
`1
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`Abstract——This paper desciibes an objective evaluation for coding
`performance of an interfrnm encoder (NETEC-22H). Also described
`is the coding performance improvement hy,,aIr adaptivubit sharing
`multiplexer (Al§S—MUX) in which transmission bit rate is dynamically
`allocated to several channels.
`V
`Measurements made for actual broadcast TV programs over a time
`‘ of 36 htshow that an SNR of higher than 50 dB unweighted is obtained
`by this coding equipment for 99 percent of the time for broadcast TV
`programs at the ‘transmission bit rate of 343 Mbits/s and {M93 percent
`of the time at 20 Mbits/s. The residual 1 percent at 30 Mhits/5 or 7
`percent at 20 Mhits/s is transmitted with a slightly lower SNR. The‘,
`picture quality difference between the 20 and 30 Mbitfs transmission
`is about 6 dB in SNK on.tbe average.
`It is also shown that a three-channel ABS-MUX (20 Mhits/s per
`channel on the average) reduces probability of coarse quantization by
`a factor of 5-10 compared with the fixed bit rate transmisflgon at 20
`Mbits/s.
`
`1. INTRODUCTION
`
`ARIETIES of television coding algorithms have been de-
`Vvised and developed [1] , [2] . lnterframe coding has been
`expected to be most promising [3}. At first, it was applied to
`1 MHz video telephone for face-to-face communication {4} . In
`‘due course, the application was extended to 4 MHZ video tele-
`conferencing. Interframe coding has‘ paved the way to visual
`communication with full motion video [5] —{10} .
`Until now, emphasis has been placed on achieving a high
`compression ratio for video teleconferencing application. On
`the contrary, as far as broadcast TV signal transmission is con-
`cerned, it is more important to transmit a high quality signal
`than to achieve a high compression ratio. Some examples are
`mentioned in the literature of such digital television encoders
`for broadcast TV program transmission use at 16-30 Mbits/s
`[11] -'-[13] .
`The interframc encoder (NETEC-22H) described here is an
`improved version of that described in [1 l ] , in which an adap-
`tive interframe/intraframe prediction is used to improve coding
`performance for pictures with substantial motion [14]. Ac-
`cording to subjective evaluation, encoded picture quality is
`excellent for most pictures at a coding bit rate of 20-30 Mbits/s.
`However, if a very busy picture with active motion is supplied,
`some picture quality degradations are observed, although they
`are enccriintcred with a very small probability in actual tele-
`
`rnccivccl March 13, 1981; revised August 5, 1981. This
`5/laririscript
`paper was prcscntcd in part in the National ‘lclecommunicatiorts Con-
`ference, Dallzizs, TX, lieccrnbcr U76, and the International Conference
`rm i:T)ITlmLllli!,'illi(Ji']5l, Boston, MA, June 1979.
`The autliurr arc with Nippon l*lcL:triv Cmnparnv,
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`l,ttl., Kziwzisaki,
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`-the interframe coding performance
`vision programs. Thus,
`greatly depends upon picture content.
`>
`1
`in order to obtain an objective measure of the intcrframe
`coding performance, knowledge of the statistics of TV signals
`is necessary.
`in this paper, probability distributions of the
`amount of information encoded by NETEC-22I,;I [l5]
`are
`measured for actual broadcast TV signals for many hours.
`Also, statistics of the encoder parameters, which‘are adap-
`tively controllcd according to the buffer memory occupancy
`or equivalently the rate of source signal information, are meas-
`ured. These results are exploited in calculating SNR probabili-
`ties of encoded broadcast TV signals. Furthermore, effective
`utilization of transmission bit rate and picture, quality im— '
`proverncnt can be achieved by means of the proposgd adaptive
`bit sharing multiplexer (ABS-MUX) for multiple simultaneous
`channel transmission {16} , using the advantage of instantaneous
`differences among multiple channels which are statistically
`‘similar. The effect of ABS-MUX is: also measured for actual
`broadcast TV signals by using physically realized hardware
`systems.
`'
`'
`i
`ll. CODlNG Al.GORlTHM
`
`The encoder/decoder block diagram is shown in Fig. 1. A
`composite NTSC color TV signal
`is normally sampled at
`iO.76 MHZ and digitized into an 8 bit PCM signal, and then
`compressed to reduced bit rate data of 2-3 bits/picture ele-
`ment (bit/pel) on the average through digital signal processing.
`First, the preprocessor makes compensation for the phase in-
`version of the color subcarrier between two successive frames.
`The adaptive interframe predictive encoder removes redundancy
`from the signal by adaptive prediction and the variable word-
`length coder compresses prediction error information with
`variable wcrdlength codes. The compressed data stream, which
`is generated irregularly, is smoothed out by the buffer memory
`and sent to the transmission line. At the decoder, the inverse
`
`processing is made to reproduce the NTSC color TV signal.
`The variable wordlength decoder expands the compressed
`data supplied from the buffer memory. The expanded data
`is decoded through the adaptive interframe predictive decoder
`to yield the phase-compensated signal. The postproccssor pro-
`duces the composite NTSC color TV signal to be D/A con-
`verted.
`
`Thus, the codec is designed so that the composite vidco sig-
`is directly encoded and the waveform of the input signal
`nal
`is preserved except for qll‘.1l1il‘Z1lli()l) el'l'cc.L
`The L‘l1CO(.lP,l/d(?t‘l)tlt3l‘ operates under twodil"l‘cs'c11i sampling
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`KOGA et’al.: PERFORMANCE ANALYSIS or INTERFRAME ENCODER
`
`Buffer Memory Occupdncy KBMO)
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`l. NEYEC-22H encoder/decoder hloci: diagram. BMO (*)
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`quency) in T-mode and 7.16 MHz (456 X f},-) in S-mode. The
`T-mode is a normal operation mode. The S-mode is a sub-
`_
`_
`_
`_
`Nyquist frequency operation which is only applied for ex-
`treme cases where a large amount of information is generated
`and buffer fill occurs or is likely to occur. Therefore, T-mode
`operation is mainly described in what follows.
`A. Subc-arrier Phase Compensation
`
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`Since the subcarrier phase of the NTSC color TV signal
`alternates by 1800 31 3 Sampling Point: frame by ffamea Sub‘
`carrier phase compensation is necessary before taking frame-
`to-frame differences.
`
`Basically, the input composite signal is,f1rst separated into
`luminance and chrominance components,/and then the phase
`of the chrominance component signal is/inverted every other
`frame to produce a phase-compensateh signal. The phase-
`compensated signals Ym and Cm are encoded through the
`interframe coder as follows. Shown in Fig. 2 is the preprocessor,
`consisting of an orthogonal transformer for T~mode and a ’
`comb filter for S-mode. In the orthogonal transformer (OTF),
`a pair of lines L2", and L2,,,$1 are used to yield luminance
`Y," and phase-compensated chrominance Cm components by
`the following second-order orthogonal transformation.
`
`Y“ =1
`
`2
`
`C
`
`(—l)" *("1)
`
`_1n
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`.[L‘”']
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`L2m+1
`
`\
`
`(1)
`
`1
`
`where n is a frame number and the operation (—1)" corre-
`sponds to the phase inversion to be made every other frame.
`At the decoder, the inverse transformation of (1) is made
`to reproduce the composite signal L2," and L2,,” 1.
`
`A L2m
`1.2,...
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`Cm '
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`P6
`hase com nsation represented
`It should be noted that the
`by (1) and (2) produces no distortion, because it is a reversible
`process.
`In the comb filter for S-mode, chrorninancc (C) and lumi-
`nance (Y) components are separated using 21 l[[ delay circuit
`and a bandpass filter. 'l'lv: phase of the chmminzmce signal C
`
`
`
`S‘modQ
`Preprocessor for subcarrier phase compensation.
`
`Fig. 2.
`
`is inverted etery other frame and added to the low-pass filtered,
`Y to yield a phase compensated color TV signal. Strictly speak-
`ing, this process gives rise to slight degradation in color fidelity
`because it is irreversible.
`«
`
`B. Adaptz've,Predicz‘z'on Irzterframe Coding
`
`l)Predr’cn'on Function.‘ A block diagram of an adaptive in-
`terframe predictive encoder is shown in Fig. 3. The coder has
`two predictors. One is an interframe predictor, P,(z), and the
`other is an intraframe predictor,P2 (2).
`Using the Z-transform representation
`
`P'1(z) =2‘ F,
`-3z
`
`P2(Z)= Z_,
`
`for Tamas-mode
`
`,
`
`for T-mode
`
`for S-mode
`
`F
`
`3
`one frame delay.
`where 2‘ means three sample delay and 2”
`A more nearly optimum prediction function could be deter-
`mined [1], [17], but the simple function P; (Z) above is used
`for the sake of hardware simplicity. The simplification results
`in an increase in the amount of information by only 5 percent.
`The adaptive prediction is made by exclusively choosing one
`of the two predictors.
`The choice of the prediction functions is made according to
`the quantized prediction error amplitude. if the prediction er-
`ror is smaller than a threshold level T11, the present switching
`signal is continued in order to hold the same prediction. When
`the quantized prediction error amplitude exceeds TH, the pre-
`diction switching sigrml
`is irlverlcrl in polarity by EX-(_)l{f ate,
`
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`

`
`IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. C(")M-29, NO. 12, DECEMBER 1981
`
`8(Mali)
`
`‘(rm/pot)
`
`lntra=!rsmo(2"l
`
`<
`Fig. 3. Adaptive interframe predictive encoder.
`x
`
`V and the prediction is switched to the other. Thus, the choice
`is made on _a sample-by-sample basis. For stillparts of the pic-
`tures,‘ the interframe prediction error is almost zero. Con-
`versely,_it
`is larger than intraframe predictionerror for the
`moving parts. On account of these prediction error properties,
`the adaptive prediction algorithm gives nearly optimum predic-
`tion, since the interframe coding is used for still parts of pigs-
`tures and the intraframe coding is used for moving parts. it is
`notnecessary to trapsmit the prediction switching information
`because it
`is included in the magnitude of prediction error
`which is transmitted. The optimum value of TH depends upon
`picture contents, but a value around 10,/256 is nearly optimum
`for most pictures.
`‘
`This adaptive algorithm provides better coding performance
`than the former NETEC-22H algorithm [ll] based upon the
`third previous sample difference of the frame difference tech-
`'nique. Computer simulation results are shown in Fig. 4, where -
`a picture is panned at a speed of 0-11 pels/frame. Fig. 4 shows
`that the coding performance of this algorithm is high compared
`with that of interframe,
`intraframe, and the third previous
`sample difference of the frame difference coding‘ techniques.
`Particularly, the improvement by the adaptive predictions is
`prominent for pictures panned at high speeds. As the speed
`becomes higher,
`the probability of interframe predigtion
`being selected tends to be 0.5. A theoretical analysis based upon
`a simpld signal model gives a result which agrees with the simu-
`lation study [18].
`v
`2) Nonlinear Function (NL): A nonlinear function NL is
`applied to the frame difference signal, taking a key role in im-
`proving the coding performance. The number of significantly
`changed pels caused by signal noise and quantization noise is
`greatly decreased by applying NL. Thenonlinear function has
`an input-to-output relation as shown in Fig. 5. The transfer
`gain is less than unity for small input amplituderand unity for
`large amplitude. When the transfengain of the frame difference
`path is less than unity, the loop transfer function of the inter-
`frame coding has a recursive type low-pass characteristicalong
`the temporal axis. The low-pass filtering suppresses random
`noise in the input signal which would otherwise cause un-
`wanted changed picture elements even for still parts of pic-
`tures. wcurring quantization noise is also suppressed through
`the temporal low~pass filtering.
`The nonlinear characteristic as shown in Fig. 5 is useful be-
`cause small amplitude noise in the still parts of pictures is sup-
`pressed through the temporal low-pass filtering. and large amp
`
`
`
`
`
`PredictionErrorEntropy
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`Fig: 4. Comparison of four kinds of prediction methods.
`
`Output
`
`V
`
`Fig. 5.
`
`Input-to-output characteristics of nonlinear function NL.
`
`.
`
`(ll/256)
`
`litude frame differences caused bymotions are not affected at
`all. The nonlinear function causes distortion in pictures with
`small brightness change from frame to frame. The effect is
`hardly seen in NLI and NL2, although it may be perceived in
`NL3.
`,
`F
`‘
`The influence of the nonlinear function on static perfonn-
`ance measures such as differential gain (DG) and differential
`phase (DP) is small. The results obtained show that DG is 2
`percent and DP 10°. The signal-to-noise ratio measured for a
`15.734 kHz sinusoidal wave input is 55 dB weighted, which -
`meets the broadcast picture quality requirement.
`3) Quantizirzg Characteristics.‘ Since the amount of infor-
`mation generated by the interframe coder varies with picture
`contents, it should be controlled to prevent the buffer memory
`from overflowing and underflowing. The information genera-
`tion rate ‘can be controlled by changing quantizing character-
`istics as well as other parts of the algorithm. In other words,
`the information rate can be controlled at the cost of picture
`' quality. Generally, if the quantiring step size is doubled. the
`infornration rate is decreased by I bitfpel. In this encoder.
`eight quanli'I,crs. Q0—Q7, are used to provide a gradual control.
`
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`KOC-A et'al.: PERFORMATTCE ANALYSIS OF INTERFRAME ENCODER
`
`TABLE I .
`,
`QUANTlZlNG CHARACTERISTICS OF Q0, Q1, AND Q2
`Ouarmzar Output Levels
`(x 5/255)
`,0 L0 2.0 3.0 40520 so 70 so so iO5....,l27.5
`0 L5 so 45 6.5 5.5 nos :55 his use
`025 5075 105 I35 155......
`
`and one of them is adaptively selected by feedback control
`tisingbuffer memory occupancy (BMO) values.
`4
`The quantizing characteristics of the Finest three quantizers
`Q0, Q1, and Q2 are shown in Table I. The quantizing step size
`of-the finest quantizer Q0 is l.0/256 for small amplitude, pro-
`viding an 8 bit PCM equivalent quality for small amplitude
`change. Those of Q1 and Q2 are 15/256 and 25/256, respec-
`g tively. The number of quantizing levels-is 61 in Q0. The maxi-
`mum output level is ‘chosen to be 127.5,/2565.,-'~which is large
`enough to prevent slope overload.
`‘
`'
`SNR representation of picture qpality for these quantizing
`charaeteristigs is made by assuming that the SNR is given by
`the minimum quantization step size, although the quantizing
`characteristics are nonuniform. When the peak-to-peak lumi-
`nance amplitude (Vpp) is set to be 142/256, the relation be-.
`tween SNR and the quantizing step size (S/256) can be expres-
`sed by the following equation.
`
`SNR é 20 log“) (Vpp iV,m5).
`= 53.8 — 20 log, 0 S‘
`
`’
`(dB unweighted)
`
`where
`
`m_ JV,ms =5’/V 12.
`
`Accordinglto the -equation, quantizers Q0, Q1, and Q2 pro-
`vide the SNR values of about 54, 50, and 46 dB unweighted,
`respectively.
`"
`e
`
`C. Variable Wordlength Cgding
`
`’In the iriterframe predictive encoding, the prediction error
`-
`isquantized and coded into a code with 6 bits/sample. The
`codes are transformed into reduced bit rate data through the
`variable wordlength coder.
`‘
`The function of the variable wordlength coder is block
`coding for the significant pel positions and variable length.
`coding for the significant pel amplitude. The variable length
`code has two sets of codes. One is a variable wordlength code
`set with the code length ranging from 1
`to 12 bits. The unit
`length code is assigned to insignificant pels. This variable
`length. code set is similar to a Huffman code and provides in-
`formation amounts almost equal to entropy values. The other
`is a fixed-length code set with 6 bit ldngth, which is used in
`conjunction with the variable one in order to avoid the con-
`tinuation of long codes. Transition between the two codesets
`is determined by comparing the prediction error amplitude
`with a certain threshold level. The transition information is
`not needed at
`the receiver. The use of these two code sets is
`particularly effective for encoding pictures with violent mo-
`tions or detailed patterns because long codes are otherwise
`generated in these pictures.
`
`Butter Memory Occupancy (MO)
`0 io2'o3o4o5oeoroeo_9oioo(%J
`r—+—o——+——t~—-+———+-—+—l—~—+——l
`
`O
`
`S‘
`
`1-/5 [¢———e~ T-mods
`——— 00
`4-502
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`ML
`
`4% NLl
`«-6 ML 2'
` ~ NL3
`
`Fig. 6. Mode control diagram.
`
`Furthermore, continuation of the insignificantly changed
`picture element code is deleted by block coding. Picture ele-
`ments are divided into unit blocks. If all the samples in the
`unit block are changed insignificantly, the unit block is de-
`leted. The positions of the deleted unit blocks are represented
`by block" address codes. The use of block address codes is quite
`useful for efficiently encoding still parts of pictures.
`. Thus, the variable wordlength coder is capable of reducing
`tlieéiganiount of encoded data with high efficiency, for all
`still, moderate, and active pictures.
`
`1). Coding Parameters Control
`
`Since the rate of encoded information varies with picture
`content, it
`is necessary to smooth out the irregular data gen-
`erationby using the buffer memory. The capacity ofthe,buf-
`fer memory is determined from the propagation delay time
`tolerated by communication links. The buffer capacity used is
`about i Mbit.
`‘
`"
`
`The control of the coding parameter combination among
`quantizers, nonlinear
`functions. and T/S-mode is made ac-
`cording to buffer memory occupancy (BMO) values. The con-
`trol diagram is shown in Fig. 6.‘ The BMO value is expressed in
`terms of precentage occupancy. The combination ofNL] and
`Q0, for instance, is used for the BMO value ranging from 0 to
`l5 percent. This combinfiation provides the best picture quality,
`equivalent to the 8 bit PCM accuracy. As BMO increases, the
`coarser quantizers are used. That is, the significance determina-
`tion level varies depending upon BMO values. Transition be-
`tween T-mode and S-mode operations occurs at the BMO value
`of about 55 percent. When S-mode operation occurs for large
`BMO values, only a slight degradation may be perceived in the
`horizontal resolution, although it is rare. The combinations of
`the coding parameters are determined, after examination for
`varietiesof pictures, so that the relation between picture qual-
`ity and the rate of encoded information can be made optimum.
`
`III. NETEC-22H CODING PERFORMANCE FOR
`BROADCAST TV PROGRAMS
`A. Statistical Measurements
`
`Coding performance is often represented by the resulting
`SNR. However, in interframe coding. SNR varies with plCl1lI‘(‘.
`contents to l)C“€ll(‘.(lLll’f(l because quantizirig characteristics are
`changed according to the rate of generated informa_tion. As
`there is no qualified objective evaluation method for motion
`
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`
`‘IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. coM-29, NO. 12. DECEMBER 1981
`r
`,
`
`many children are always running around, and cameras are fol-
`lowing them or frequently switched. Because of the motion of
`the children and of the camera, the cumulative probability at
`20 Mbits/s decreases to 73'percent. However, the cumulative
`probability at 30 Mbits/s is 99 percent. “Super Bowl ’79” was
`the most active program encountered in the rneasurement.
`This program is a football game, which was broadcast in Japan
`in Janrpry 1979 after reception via satellite relay and was re-
`cordediin a U-matic VTR from the off-the-air signal. For this
`program, the cumulative probability at 20 Mbits/s is 35 per-
`cent; however, it is still 96 percent at 30 Mbits/s. The average
`information rate is as high as 23.5 Mbits/s, being l§.3 Mbits/s
`higher than that of “Art Lecture.” The above data indicate
`the range of broadcast TV signal source variations.
`"
`The long-time average probability density‘ function P(X0)
`over 36 h is shown with a broken linein Fig. 7. The mean
`value of this average distribution is no more than 15.3 Mbits/s.
`The probabiiity of the rates greater than the average value
`rapidly decreases, and a small peak is seen at around 30-40
`Mbits/‘s. This smali peak is due to scene changes. It is interesting
`that the shape of this distribution is quite similar to that ob-
`tained by Seyler [19] ._ where the number of significant frame
`difference pels was used as ameasure of ‘information rate.
`The bold solid line, representing the cumulative probability
`of the average distribution, shows that 93 percent of .the pro-
`gram materials can be encoded at 20 Mbits/s and 99 percent
`of them can be encoded at 30 Mbits/s when a quantizing char-
`acteristic Q1 (NL1) is used. With a quantizer coarser than Q1,
`the rate of generated” information becomes smaller. Therefore,
`when the adaptive control is operated, the residual probability
`of 7 percent at 20 Mbits/s and 1 percent at 30 Mbits/s will be
`transmitted by using coarser quantizers providing slightly
`lower SNR.
`"
`*“““
`
`B. Information Generation Control
`
`in the encoder under normal operation, quantizing dharac-
`teristics are adaptively changed in order to control the rate of
`the information generation. As “Super Bowl ’79” is an ex-
`treme case and gives a very large information rate, it is used as
`an example to show the performance under feedback control.
`The probablity distributions of information rates with three
`different quantizers, Q0 (NL1), Q1 (NL1), and Q2 (NL2), are
`compared in Fig. 8. The average values with the three quan-
`tizers are 28.6, 23.5, and 16.7 Mbits/s, respectively. Then the
`difference between 'Q0 and Q1 isabout 5 Mbits/s and that
`between Q1 and Q2 is about 7 Mbits/s. These results show the
`effectiveness of changing quantizing characteristics to control ,
`information generation. It can be calculated from Fig. 8 that
`when the adaptive coder parameter control
`is made at the
`transmission bit rate of 30 Mbits/s, 82 percent of the program
`is transmitted with Q0, 14 percent with Q1, and 3 percent”
`with Q2, respectively. The residual percent is transmitted by
`using coarser quantizing characteristics
`than these three.
`About half of the residual
`1 percent is considered to be due
`to scene changes.
`‘
`At the moment of scene cliangcs, frame-to~franic correla-
`tion will be lost in general and. tlicrcfore. the intrafranic pm.
`diction will be used in the adaptive predictive encotler. The in-
`
`was
`
`PMC Exhibit 2010
`
`Apple v. PMC
`|PR2016-00753
`
`Page 5
`
`Long-grime Average
`
`"PLAYING CHILDREN"
`
`\\X
`
`\;
`
`"ART LECTURE"
`
`‘I
`El7
`/- Long-time
`'1
`Average =P(Xa)
`
`I E
`
`.
`
`
`
`ProbabilityoflntovmoiinnRateThe!ExceedsX0Mn/s
`
`l
`
`0
`
`H)
`
`Information Flatt
`
`{Xe}
`
`(Mb/sl
`
`‘OJ
`
`Fig. 7.
`
`Statistical information rates (Q1, A/Ll). P(X0) is a long-time
`average probability density function.
`
`' video at present, coding performance is evaluated from source
`signal statistics about"information rate ‘and coding parameter
`statistics.
`‘
`In order to estimate information content, the coder param-
`eters are fixed so that a certain picture quality is provided,‘
`then the probability distribution of the rate of generated infor-
`mation is measured for actual television signals for many hours.
`From the probability distribution thus obtained, the proba-
`bility of providing the picture quality at a given transmission
`bit rate is calculated. In the measurements, information rates
`per frame were measured at the output of the variable word-
`length coder (point A shown in Fig. 1) with coding parameters
`fixed; i.e., no feedback control. One quantizing characferistic,
`Q1, which provides an SNR of 50 dB unweighted slightly
`better than broadcast picture quality for long-haul transmis- ,
`sion, is used constantly in conjunction with NLl under T-mode
`operation. Measurements were made for about 36 h applying
`off-the-air TV signals from four different broadcasting sta-
`tions, received by a TV receiver. The SNR of the received TV
`signals was about 40 dB, and random noise was perceptible.
`The cumulative probabilities of information rates obtained
`for three typical programs and the long-time average distribu-
`tion are shown in Fig. 7. Here, the information per frame is
`multiplied by 30 (frames/s), and the horizontal axis is expres-
`sed in Mbits/s. The three fine solid lines are examples showing
`that generated information rates are cdnsiderablypdifferent be-
`cause of different ‘image activities.
`“Art Lecture" is an example of inactive pictures, in which
`most of the time is occupied by still or almost still pictures.
`This cumulative prbbability distribution shows that 99 percent
`of the program material can be transmitted at 20 Mbits/s by
`using Q1 (NLI) because the probability accumulated from 0
`to 20 Mbits/s is 99 percent. The average information ratein
`this program is as low as 8.2 Mbits/s. In “Playing Chiltlren,“
`
`PMC Exhibit 2010
`Apple v. PMC
`IPR2016-00753
`Page 5
`
`

`
`KOGA er 111.: PERFORMANCE ANALYSIS OF INTERFRAM’E ENCODER
`
`loo '
`
`X’
`
`/'
`
`#
`
`‘
`
`NETEC—22H eucooea '
`
`I 73
`
`NETEC-BZH DECODER '
`
`r
`
`8
`
`6
`
`
`
`ProbabilityatlnlormaiianRateThatExceedsXoMb/5
`
`.
`
`SUPERBOWL "
`
`O= Ouantuzer
`
`Fig. 9:, Threechennel transmission system configuration with ABS-
`MUX.
`
`.0
`
`Fig. 8.
`
`-‘F
`IO
`
`r
`20
`Information Plate
`
`30
`(X9)
`
`»
`V
`45
`450
`(Mb/5)
`
`Generated information rates for “Super Bowl ’79” by three
`different quantizers.
`
`formation rate in the case of “the intraframe prediction ranges
`mostly from 3 to 4 bits/pel when Q} is applied. This means
`that, at 30 Mbit/s transmission, the excessive information of
`1-2 bits/pel can be suppressed by using quantizers Q3-.—Q4.
`Then, the scene change influence on picture quality is an SNR
`decrease to 46-40 dB unweighted. In this case, the BMO value
`is raised to about 50 percent (see the control diagram in Fig.
`6). After scene changes, the influence will disappear within a
`few frames.
`'
`'
`
`as
`
`IV. ADAPTIVE BIT SHARING MULTIPLEXER (ABS-MUX)
`A. ABS-MUX Principle
`
`It has been shown that the long-time average of encoded in-
`formation is about 15 Mbi'ts/s. The probability of information
`rate greater than the average rapidly decreases as the rate in-
`creases. This
`indicates that busy pictures with large-scale
`rapid motion are not frequently encountered, and that they
`rarely appear at the same time among programs from different
`stations.
`
`Therefore, more effective channelutilization can be achieved
`by multiplexing data from multiple encoders based upon an
`idea similar to TASI [20]. ABS-MUX multiplexes plural chan-
`» nels by adaptively allocating a bit rate to each channel depend-
`ing upon individual information rates, while the total bit rate
`is kept constant [16] .
`The block diagram of the three-channel ABS-MUX system
`is shown in Fig. 9. Receiving the BMO (buffer memory oc-
`cupancy) value from each encoder, ABS-MUX decides the ‘bit
`rate to be assigned to each encoder with the total bit rate kept
`constant at 60 Mbits/s. The average hit rate per channel is
`20 Mbits/s in the three-channel ABS-MUX and 30 Mbits/s in
`the two-channel. ABS-MUX. The hit rate assignment decision
`is made every 153.6 us, one ABS frainc time. The ABS frame is
`
`Photograph of a transmission system with ABS-MUX. (From
`Fig. l0.
`left to right. three l\ETEC-22H encoders, ABS-MUX/DEMUX, four-
`phase PSK ‘modem, and two NETEC-22H decoders.)
`
`composed of 18 unit frames, with each unit frame consisting
`of 256 X 2 bits. The bit rate assignment is made by changing
`the number of unit frames assigned to each channel in one
`ABS. frame. Since one ABS frame has 18 unit frames, the as-
`signed bit rates are combinations among 16.7, 20.0, 23.3, and
`26.7 Mbits/s. For instance, 16.7 Mbits/s corresponds 10 five
`unit frames in one ABS frame.
`
`B. ABS-MUX Operation
`
`A photograph of the ABS-MUX system is .shown in Fig. 10. ~
`The photograph shows, from left to right, three NETEC-22Hv ‘
`encoders, the ABS-MUX, a four-phase PSK modem", and two
`NETEC-2211 decoders.
`'
`.
`.
`.
`
`_
`
`Two system operations are considered here: two-channel
`and three-channel ABS-MUX systems.
`5
`2'
`ABS-MUX operation measurements are inade forthese two
`system configurations by using the hardware system. Different
`broadcast TV programs are supplied to the encoders, and the
`bit rate assignment is made by ABS-MUX. ABS-MUX opera- ’
`tion was measured by monitoring the BMO values of the en-
`coders simultaneously for 5.5 h.
`.
`‘
`_The’ probability distribution of bit rates assigned to one of I
`the encoders is shown in Fig. 11. In the three-channel ABS»
`MUX case, the probabilities 0f$traI1srnissi()n at 16.7; 20.0, 23.3,
`and 26.7'Mblts/s were 9.08 percent, 77.71 percent, 12.07 peiw 7
`cent, and 1.14 percent, respectively. The probabilities of bit;
`rates assigned for the three encoders are similar‘. The average
`bit
`rates of the three encoders arc 2.0.18. 2.0.01. and 19.81 _
`Mbiis/s. nearly equal to the fixed bit rate. These indicate that
`S’
`
`PMC Exhibit 2010
`
`Apple v. PMC
`|PR2016-00753
`
`Page 6
`
`PMC Exhibit 2010
`Apple v. PMC
`IPR2016-00753
`Page 6
`
`

`
`_
`‘
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`IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. COM—29, NO. 12, DECEMBER 1.1981
`100
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`Performance improvement by ABS-MUX. (a) Three-channel
`ABS‘-MUX. (b) Twmchsrmel ABS—MUX.
`I
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`
`DENSITV ' so
`PROBABILITY
`
`55
`so
`no
`Estimated SNR (d8 unweighted)
`
`Fig. l3.
`
`SNR representation of NETEC-22H and ABS—MUX perform-
`ance.
`‘
`
`reduced greatly. In the 30 Mbit/s transmis-
`degradation is
`sion case shown in Fig. l2(b), there is little difference between
`the fixed and the ABS-MUX transmission. Probability of large
`BMO values was almost zero even in the fixed bit rate case.
`
`D. SNR Representation
`
`,» As stated before, evaluation of the interframe coding per-
`formance is a difficult problem, since SNR varies with picture
`contents and SNR is partly improved through the nonlinear
`temporal filtering for still parts of pictures.
`‘
`Here, in order to obtain an objective measure, an SNR esti-
`mation is made from the BMO statistics. Fig. 13 shows the
`estimated SNR probability calculated from the BMO statistics
`in Fig. 12(2) and (b), using the relation among BMO values,
`selected quantizers, and corresponding SNR values [see Fig.
`6 and (3)] . It is seen by summing probabilities for worse SNR
`that the cumulative prgbabflity of pictures being transmitted
`with SNR values equal to or greater than 50 dB unweighted
`was 99 percent in the.30 Mbit/s transmission case. The SNR
`probability curve estimated for the 20 Mbit/s transmission
`case is about 6 dB lower than that for the 30‘Mbit/s case. This
`is a reasonable value since the bit rate difference is nearly equal
`to 1 bit/pel, corresponding to 6 dB in SNR.
`As far as the average SNR is concerned, ABS-MUX provides
`only a slight improvement. However, it should be noted again
`that, in 20 Mbit/s coding, the occurrence of such an objection-
`aoly low SNR as 33-40 dB caused by Q4, Q5, etc., can be
`greatly reduced by using ABS-MUX.
`Thus, it can he said that ABSMUX is useful particularly in
`"the lower bit rate range. At the higher bit rate, the effect be.-
`comcs less obvious.
`Ilow«‘.v<‘r, a variety ot‘pic1i1re contents
`may be involved in lriuadczisl TV sigitnls.
`'1l'herefore. the two