# Patent

## Title
Scalable MPEG video/macro block rate control

## Abstract

A scaleable macro block rate control method particularly well-suited for MPEG video. There is provided a method to easily derive a quantization parameter (QP) value using information such as bit usage, previous QP values and SAD values from the past encoded and future frames. The method utilizes quantization estimation techniques based on statistical relationships between different intensity measures, such as distortion intensity, absolute difference intensity and mean of absolute difference intensity. The method is well-suited to applications utilizing MPEG video such as MPEG-1, MPEG-2, MPEG-4, JVT/H.264 standards and so forth.

## Background
CROSS-REFERENCE TO RELATED APPLICATIONS
This application is a continuation-in-part of application Ser. No. 10/943,551 filed on Sep. 17, 2004 now abandonded, incorporated herein by reference in its entirety, which claims priority from U.S. provisional application Ser. No. 60/541,340 filed on Feb. 3, 2004, incorporated herein by reference in its entirety, and from U.S. provisional application Ser. No. 60/554,533 filed on Mar. 18, 2004, incorporated herein by reference in its entirety. Priority is claimed to each of the foregoing applications.
Statement Regarding Federally Sponsored Research or Development
Not Applicable
Incorporation-by-reference of Material Submitted on a Compact Disc
Not Applicable
Notice of Material Subject to Copyright Protection
A portion of the material in this patent document is subject to copyright protection under the copyright laws of the United States and of other countries. The owner of the copyright rights has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the United States Patent and Trademark Office publicly available file or records, but otherwise reserves all copyright rights whatsoever. The copyright owner does not hereby waive any of its rights to have this patent document maintained in secrecy, including without limitation its rights pursuant to 37 C.F.R. §1.14.


BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention pertains generally to video coding and decoding techniques, and more particularly to methods for scalable macro block layer rate control and picture layer rate control for MPEG video.
2. Description of Related Art
In real video applications, where either a real-time streaming mode or a non-real-time batch mode is used, constant video quality is a goal in developing a rate control scheme. Although the first order and the second order rate distortion models for these two modes provide a good foundation for target bit rate estimation and quantization parameter (QP) estimation, the fluctuation in target bit rate and quantization parameter values derived from the model generates unstable video quality, resulting in worse viewing quality.
Therefore, a need exists for a scalable rate control method that is simple to implement and that results in better viewing quality. The present invention provides these benefits and overcomes the drawbacks of prior methods.
BRIEF SUMMARY OF THE INVENTION
Video coding and decoding techniques are described for scalable macro block (MB) layer rate control and picture layer rate control for MPEG video, including but not limited to, MPEG-1, MPEG-2, MPEG-4 and JVT/H.264 standards. According to an aspect of the invention, there is provided a method to easily derive a quantization parameter (QP) estimation value using information such as bit usage, previous QP values and sum of absolute difference (SAD) values from both past encoded and future frames.
In one embodiment, the method comprises the steps of calculating the average bit count (AvgTargetBitP) obtained in a “bit allocation” module (using future frames); calculating the previous bit count (ActualBitPrv) (using past encoded frame); calculating the target quantizer scale (Qscale) using AvgTargetBit and ActualBitPrv to adjust the deficit/surplus bit rate budget; refining Qscale using SAD statistics from past encoded frames and current buffer status; and bounding Qscale in the range of pre-defined MinQP and MaxQP values.
Another aspect of the invention is to provide for scalable macroblock rate control for quality improvement based on picture contents and coding complexity. In one embodiment, the method comprises the steps of initialization wherein, for example, data members can be initialized, image dimension information can be set, and working memory can be allocated; performing an iRateCtrlMbBootUp step which can comprise obtaining the picture level target QP from picture level rate control, calculating each MB content complexity (MbMad) and average Mad, determining the intensity base, and determining the local adjust range; performing a Mode Decision step which comprises calculating InterAD and IntraAD, and possibly determining the final mode and its QP; performing a iRateCtrlMbCalcComplexitylonly step which comprises obtaining IntraAd from mode decision module, calculating the MB-level QP in I-slice, sending this QP back to mode decision module; performing a iRateCtrlMbCalcQp step which comprises obtaining IntraAd and InterAd from the mode decision module, calculating two MB-level QPs, IntraQp and InterQp, for Inter mode and Intra mode, respectively in P-slice, and sending the two QPs to the mode decision module; performing an iecMbCoding step which comprises encoding the current MB; performing a vRateCtrlMbUpdate step which comprises accumulating QP, Ad and the number of coded MBs, checking mode coding where if there is no mode MB coding, returning to the mode decision module or otherwise proceeding to the next step; and performing a vRateCtrlMbAfter step which comprises calculating the distortion of the current frame, calculating the average Ad for the next frame, and calculate the average LocalAdj for the next frame.
Further aspects of the invention will be brought out in the following portions of the specification, wherein the detailed description is for the purpose of fully disclosing preferred embodiments of the invention without placing limitations thereon.



BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
The invention will be more fully understood by reference to the following drawings which are for illustrative purposes only:
FIG. 1 is flow diagram of an embodiment of a method for scalable rate control of MPEG video according to an embodiment of the present invention.
FIG. 2 is a graph showing QP as a function of buffer deviation corresponding to the left half of Table 2.
FIG. 3 is a graph showing QP as a function of buffer deviation corresponding to the right half of Table 2.
FIG. 4 is a graph showing QP as a function of buffer deviation corresponding to the left half of Table 3.
FIG. 5 is a graph showing QP as a function of buffer deviation corresponding to the right half of Table 3.
FIG. 6 is a flow diagram of an embodiment of a method for scalable macro block control according to an embodiment of the present invention.
FIG. 7 is a graph showing the dynamic range distribution of QP as a function of picture syntax QP.



DETAILED DESCRIPTION OF THE INVENTION
Referring more specifically to the drawings, for illustrative purposes the present invention is embodied in the described methods and techniques. It will be appreciated that the invention may vary as to the specific steps and sequence, without departing from the basic concepts as disclosed herein.
A. Scalable Rate Control for MPEG Video
The following discussion illustrates an example embodiment of the present invention. It will be appreciated that labels, terms, sequences and other specific parameters are used in connection with the example described herein and may be changed without departing from the scope of the invention.
1. Bit Rate Control Methodology
One aspect of the invention pertains to easily deriving a QP value using information such as bit usage, previous QP values and SAD values from the past encoded and future frames. Referring to FIG. 1, in one embodiment, this is accomplished by carrying out the following steps:
At step 10, the average bit count (AvgTargetBitP) obtained in a “bit allocation” module is calculated using future frames. Next, at step 12, the previous bit count (ActualBitPrv) is calculated using a past encoded frame. At step 14, the target Qscale is calculated using AvgTargetBit and ActualBitPrv to adjust the deficit/surplus bit rate budget. Next, at step 16, Qscale is refined using SAD statistics from past encoded frames and current buffer status. Finally, at step 18, Qscale is bounded in the range of pre-defined MinQp and MaxQp. Elements of this process are described below.
2. Execution Phase 0: Initialization
In this phase, initialization takes place, including the initial buffer status, buffer convergence factor, data arrays for collecting statistics, and specifying the minimum Qscale, RateControl sliding window.
2.1 Minimum Qscale Value Setting
The Minimum QP setting is for maintaining maximum video quality for encoding a video sequence. The Qscale value is dependent on the bit rate and frame rate. In the invention, bits per MB are used as a threshold to determine the minimum Qscale, as shown in Table 1.
3. Execution Phase 1: Pre-Encoding
In this phase, the encoder performs the following functions:

    
    
        (a) Bit rate budget adjustment;
        (b) Target bit rate estimation for the current frame;
        (c) Qscale calculation for the first I-VOP and subsequent I-VOPs; and
        (d) Qscale calculation for P-VOPs.
    
    


3.1 Bit rate Budget Adiustment
Bit allocation is performed based on the SAD values of P-VOP, B-VOP and MAD values of I-VOP. In bit allocation the first step is to calculate the total available bit budget in a Rate Control (RC) window and bit budget for a frame before encoding a frame. To monitor these two values, a sliding window based bit allocation is used, for example as follows:

//total number of bits available for this RC sliding window

TotalBudget=(DefaultGovSec*Bit rate*RC_SPAN+TotalLoan),

Wherein TotalLoan=(CurrentOccupancy−InitialOccupancy) is the amount of under-spending (TotalLoan>0) or overspending the bit budget (TotalLoan<0).
3.2 Target Bit Rate Estimation
Next, the bit allocation for a frame is determined by its frame type and the associated SAD/MAD. First, for each picture type, all of its associated SAD/MAD values are summed, and basically the bit budget for a frame with P-type or B-type is proportional to its MAD with respect to the overall MAD within a RC sliding window. To maintain a minimum quality, an average bit budget for a frame is calculated, and the MAD variation of a frame contributed to the bit budget is bounded, such as by minus and plus 15% as follows:

AvgMAD=TotalMAD/Num_of—P_Vops

AvgTargetBitP=(TotalBudget/((m—dRCWindowSize+3.7)*RC_SPAN))

Variation=limit(−0.15, (TargetMADt−AvgMAD)/AvgMAD, 0.15)

TargetBits=(int)(AvgTargetBitP*(1.0+dVariation))

After this bit allocation, the buffer fullness is taken into account by adjusting the target bits toward the initial buffer occupancy as follows:

Cushion=(PseudoBufferSizeTop−Occupancy)

Fullness=(Occupancy−PseudoBufferSizeBottom)

TargetBits=(TargetBitCur*(Cushion+ConvergeFactor*Fullness)/(ConvergeFactor*Cushion+Fullness))

3.3 QP Value for the First I-VOP
In a real application, the video quality of the first VOP plays an important role in determining the first impression of a user viewing a decompressed video sequence. Unlike MPEG-4 committee code which requires input for the first I, P and B VOPs, according to the rate control scheme of the present invention, a simple but effective assumption is made to provide a reasonable video quality of the first frame without user interaction. The QP value is determined based on the following assumption: For example, if the DefaultCompressionRatio is equal to 10:1, then DefaultQScale is reasonably equal to 5 so that the Qscale for the first I-VOP is calculated as follows:

DefaultTargetBits=Height*Width/*8/(DefaultCompressionRatio;//for Luminance part

DefaultTargetBits+=(Height*Width/2*8/(DefaultCompressionRatio*2);//for Chroma part

TargetBits=min(TargetBits, (VbvBufSize−InitialOccupancy)*0.2)

Qscale=DefaultTargetBits*DefaultQScale/TargetBits

To further refine the calculation, two difference encoding modes (streaming mode and non-streaming mode) are preferably utilized to lower the Qscale further, and bounded, such as by Qscale=8 for minimum image quality in this example.
3.4 QP Value for the Subsequent I-VOP
Besides the first I-VOP, QP values for the subsequent I-VOPs also need to be considered. Although an RD model for I-type VOP can be developed, due to its high complexity and without considering video quality of its neighboring frames, the present invention employs a simple scheme to determine the QP value of I-VOP. In accordance with the invention, the QP value depends on three factors: (1) previous QP value, (2) calculated QP value (target QP) obtained in Section 3.2, and (3) the current buffer fullness as follows:
If (Buffer occupancy−Initial Occupancy)>0, implying under-spending bits, then
If (PrevQP>TargetQP)

TargetQP=TargetQP*(1−(1-deviation)^2)+PrevQP*(1-deviation)^2) and is bounded by (TargetQP+PrevQP)/2;

If (PrevQP<=TargetQP)

TargetQP=PrevQP*(1−(1-deviation)^2)+TargetQP*(1-deviation)^2)

where deviation=(Occupancy−InitialOccupancy)/ (VbvBufSize−InitialOccupancy).

In Table 2 and FIG. 2 and FIG. 3, two examples are shown to demonstrate the Qscale calculations under these conditions. The left hand side shows that if PrevQP (e.g., 28)>TargetQP (e.g., 8), then the final QP is shown in column 5. The right hand side of the table, on the other hand, shows that if PrevQP (e.g., 3)<TargetQP (e.g., 8), and the final QP is calculated in the last column.
On the other hand,
if (Buffer occupancy−Initial Occupancy)<0//implying over-spending bits
If (PrevQP>TargetQP)

TargetQP=PrevQP*(deviation^2)+TargetQP*(1-deviation^2)

If (PrevQP<=TargetQP)

TargetQP=TargetQP*(deviation^2)+PrevQP*(1-deviation^2)

where deviation=(InitialOccupancy−Occupancy)/(InitialOccupancy).

In Table 3 and FIG. 4 and FIG. 5, two examples are shown to demonstrate the Qscale calculations under these conditions. The left hand side shows that if PrevQP (e.g., 28)>TargetQP (e.g., 8), then the final QP is shown in column 4. The right hand side of the table, on the other hand, shows that if PrevQP (e.g., 3)<TargetQP (e.g., 8), then the final QP is calculated in the last column.
3.5 QP Value for the First P-VOP
The QP value for the first P-VOP is calculated as follows. First, the target bit rate for this VOP is obtained by the bit allocation module. Then its QP can be derived from the following equation empirically. To prevent the occurrence of a sudden quality change, this QP is bounded by its previous I-VOP's Qscale, and further bounded by MinQP and MaxQP.

dQCur=(m—iActualBitPrvl*m—iQPrvl)/(8.0*m—iTargetBitCur)

dQCur=limit((double)m—iQPrvl, m—dQCur, (double)m—iQPrvl+2)

iQCur=limit(m—iMinQScale, (int)m—dQCur, m—iMaxQScale)

3.6 QP Calculation for P-VOP
To calculate a target Qscale, the following five steps are performed:
Step 1: calculate the average bit count (AvgTargetBitP) obtained in the “bit allocation” module (using future frames) as follows:

iAvgTargetBitP=(iTotalBudget/(dRCWindowSize+3.7)*RC_SPAN)

Step 2: calculate the previous bit count (ActualBitPrv) (using past encoded frame)
Step 3: calculate the target Qscale using AvgTargetBit and ActualBitPrv to adjust the deficit/surplus bit rate budget. If the previous P-VOP spent 15% more than an average bit count, then QP should be increased by its deviation. If the previous P-VOP spent around 20% less than an average bit count, then QP should be decreased by its deviation.
If none of these two conditions, then QP remains unchanged. The description of this step is pseudo-encoded as follows:















if (iActualBitPrvP > iAvgTargetBitP*1.15) {










dQCur =
(iQPrv + (iQPrv*(iActualBitPrvP−









AvgTargetBitP)/iAvgTargetBitP)*0.55 );









}



else if (iActualBitPrvP < m_iAvgTargetBitP/1.20) {










dQCur =
(iQPrv − (iQPrv*(iAvgTargetBitP−









iActualBitPrvP)/iAvgTargetBitP)*0.55 );









}



else









dQCur = iQPrv;










Step 4: refine Qscale using SAD statistics from past encoded frames and current buffer status. Refining Qscale is conjunction with buffer control and SAD statistics. In the case of over-spending bit budget (i.e., case 1), the encoder has to consider the potential buffer underflow problem by increasing Qscale. The Qscale is scaled up by buffer deviation. Besides, to further refine Qscale, SAD is used to determine the final Qscale. If the deviation of the current SAD is larger than 10%, meaning a more complex scene is on its way, thus the final Qscale should be increased by the amount of iQPrv*(dBufDeviationP/dScale, where iQPrv is the previous Qscale to take a early action before a buffer underflow occurs. If the deviation of the current SAD is smaller than about 10%, a less complex scene is expected, then the final Scale can be adjusted by its buffer status and bounded by its previous Qscale to maintain a certain degree of video quality. The following pseudo-code describes the procedure to refine Qscale:

dSadDeviationP=(dSadCurP−dAvgSadCurP)/dAvgSadCurP; 

dDifferenceP=(double)(m—iOccupancy−m—iInitialOccupancy);
















// Case 1: potential buffer underflow!!



if (dDifferenceP < 0.0) {









dScale = 1.5;



dBufDeviationP = −1*dDifferenceP/iInitialOccupancy;









if (dSadDeviationP > 0.1 ) {









dQCur = limit(iQPrv, (dQCur),



iQPrv+iQPrv*(dBufDeviationP/dScale));









}



else if (dSadDeviationP < −0.1) {









dQCur = limit(iQPrv−iQPrv*(dBufDeviationP/dScale),



(m_dQCur),



iQPrv);









}



else









dQCur = limit(iQPrv−iQPrv*(dBufDeviationP/dScale),



(m_dQCur),









iQPrv+iQPrv*(dBufDeviationP/dScale));









}










In the case of under-spending bit budget (i.e., case 2), the encoder has more room to maintain the video quality. In this case, the SAD is used to scale down the Qscale by its deviation to the average SAD values. If the deviation of the current SAD is larger than about 10%, meaning a more complex scene is on its way, thus the final Qscale will be bounded by the PrevQscale or less to maintain constant quality since the encoder has more bits available to spend. The final value of Qscale is decreased by the amount of iQPrv*(dBufDeviationP/dScale, where iQPrv is the previous Qscale. If the deviation of the current SAD is smaller than about 10%, a less complex scene is expected, then the final Qscale can be maintained to avoid sudden quality change, even though the change is directed to quality improvement. If none of the above two conditions holds, meaning a smooth scene is expected, the final Qscale is adjusted based on its buffer states.
The following pseudo-code describes the procedure to refine Qscale:












// case 2: easy mode for rate control


else {









dScale = 2.0;



dBufDeviationP = dDifferenceP/(double)m_iInitialOccupancy;



if (dSadDeviationP > 0.1) {









dQCur = limit(iQPrv−iQPrv*(dBufDeviationP/dScale),



(m_dQCur), iQPrv);









}



else if (dSadDeviationP < −0.1) {









dQCur = limit(iQPrv, (m_dQCur),



iQPrv+iQPrv*(dBufDeviationP/dScale));









}



else {









dQCur = limit(iQPrv−iQPrv*(dBufDeviationP/dScale),









(m_dQCur),



iQPrv+iQPrv*(dBufDeviationP/dScale));









}







}









Step 5: bound Qscale in the range of pre-defined MinQP and MaxQP.
4. Execution Phase 2: Encodinq
In the encoding stage, if either the frame- or object-level rate control can be activated, the encoder just simply encodes the video frame or object using the value of QP obtained in the pre-encoding stage. However, some low-delay applications may require more strict buffer regulations, for example 250 ms for the maximal accumulated delay, or higher bit rate encoding (e.g., 1 ̃4 Mbps encoding at CCIR-601 resolution), or perceptual-based encoding, then a macroblock-level rate control is expected. However, the macroblock level rate control is costly at low rate since there is additional overhead if the quantization parameter is changed within a frame. For example, in the MPEG-4 video, the MB (MacroBlock) type has to be encoded with three more bits indicating the existence of the differential quantization parameter (i.e., dquant).
Furthermore, two bits need to be sent for dquant as described in MPEG-4 documentation. For the same prediction mode, an additional 5 bits need to be transmitted in order to change QP. In the case of encoding at 10 kbps, 7.5 fps, qcif resolution, the overhead is computed as high as 99*5*7.5=3.7 kbps. If only 33 macroblocks are encoded, the overhead 33*5*7.5=1.2 kbps. Thus, there will be about 10 percent loss in compression efficiency at low bit rate encoding. At high bit rate, the overhead bit count is less significant than the residual bit count.
5. Execution Phase 3: Post-Encoding
In the post-encoding stages, the encoder simply records the statistical data such as the bit usage, MAD or SAD and the distortion of the decoded picture from its original picture. The encoder also updates a VBV buffer status. Unlike the first order or the second order rate distortion models that requires computational load for model parameter derivation.
5.2 VBV Buffer Update
To update the VBV buffer status, the channel input rate to the VBV buffer is calculated based on the lapsed time. Then if the VBV buffer fullness (i.e., ioccupancy) is smaller than the actual coded size of the current frame, then a buffer underflow occurs. To deal with buffer underflow, one solution in the present invention is to freeze the previous frame by replacing the already encoded bits with stuffing bits which basically assume all macroblocks are marked as Skip macroblocks. In the case of buffer overflow, an easy solution which involves stuffing more bits into the bitstream may be utilized. The number of stuffing bits is given by:

iOccupancy−iOverFlowLevel

Wherein iOverFlowLevel is around the size of the VBV buffer. The pseudo-code of this part is shown below:












if (iOccupancy <= (iActualBitCur+8) {









// buffer underflow



replacing the coded bits of the current frame with stuffing bits



}



else {









iNumberOfStuffingBits = iOccupancy − iOverFlowLevel;



if (iNumberOfStuffingBits > 0)









do bits stuffing (iNumberOfStuffingBits);









else









iNumberOfStuffingBits = 0;









}



Occupancy += iChannelInputRate − iNumberOfStuffingBits










B. Scalable Macro-Block Rate Control

1. Overview
The following discussion illustrates an example embodiment of the present invention. It will be appreciated that labels, terms, sequences and other specific parameters are used in connection with the example described herein and may be changed without departing from the scope of the invention.
1.1 Introduction
The macro-block rate control (MbRc) methodology of the present invention is intended -for bit rate and quality control for MPEG-4 encoders, such as the Sony MPEG-4 AVC/ITU H.264 encoder. To activate this MbRc, its picture level rate control must be enabled to pass the target QP of a frame to MbRc. Note that the methodology of the MbRc can be applied to any rate control scheme as long as the Qp value for a picture is provided. There are two versions of this implementation of MbRc. One is the floating-point implementation for high performance computing system (e.g., Intel IA-32 platform); the other is fixed point implementation for ARM based platform without powerful floating-point capability. This new MbRc is based on the notion of “intensity”, it is very simple to implement, and provides very effective performance in visual quality. A flow diagram of the methodology is illustrated in FIG. 6 wherein the MB rate control steps are shown in blocks 100, 102, 106, 108, 112 and 114.
1.2 Enabling Floating Point MB-RC
Floating point MB-RC is enabled as follows:
In StatisticalDefine.h file,
#define NEW_PIC_RC
#define_SRC_MB_//turn on MB rate control
1.3 Enabling Fixed Point MB-RC
Fixed point MB-RC is enabled as follows:
In StatisticalDefine.h file,
#define NEW_PIC_RC
#define_SRC_MB_//turn on MB rate control
In JvtScalableRateControlMB.h
#define SRCMB_INT—
1.4 Enabling Statistical Printout
Statistical printout is enabled as follows:
In JvtScalableRateControlMB.h
Prerequisite:_SRC_MB_ is enabled in StatisticDefine.h
if (defined(_SRC_MB_INFO_ONLY_) &&

    
    
        defined(_SRC_MB_PRINTOUT_) then
        MB info of PIC-level RC is recorded
    
    


if (undefined(_SRC_MB_INFO_ONLY_) &&

    
    
        defined(_SRC_MB_PRINTOUT_) then
        MB-level RC is enabled and MB info is recorded
    
    


//#define_SRC_MB_INFO_ONLY—
#define_SRC_MB_PRINTOUT—
2. MB-RC Class Structure
2.1 Data Members
The following are examples of data members used in this embodiment of this invention:














JvtRcParameter*
m_pRcParameter;
// Pointer of JvtRcParameter class









JvtPicParam*
m_pPicParam;
// Pointer of JvtPicParam class


JvtMbParam*
m_pMbParam;
// Pointer of JvtPicParam class









int
m_iMB_h;
// number of MBs in x-axis


int
m_iMB_v;
// number of MBs in y-axis


int
m_iNumOfMb;
// total number of MBs


int
m_iNumofCodedMb;
// total number of coded MBs


int
m_iPicTypeCur;
// picture type of the current frame


int
m_iRetryCount;
// retry counter


int
m_iMbAccmQp;
// accumulated syntax Qps


int
m_iMbQpCur;
// syntax Qp of current MB


int
m_iMbQpPrv;
// syntax Qp of previous MB


int
m_iPicEstSyntaxQp;
// estimated Qp from PicRc


int
*m_piMbMad;
// a pointer to a Mad map


int
m_iMbAvgMad;
// average Mad of a slice(frame)


int
m_iMbAvgAd;
// average Ad of a slice(frame)


int
m_iMbTotalAd;
// total Ad of a slice


int
*m_piMbDistortionMap;
// a pointer to a distortion map


int
m_iMbIntraAdCur;
// IntraAd of current MB


int
m_iMbInterAdCur;
// InterAd of current MB


int
m_iMbIntraQp;
// IntraQp of current MB


int
m_iMbInterQp;
// InterQp of current MB







#ifdef _SRC_MB_INT—








int
m_iQpScale;


int
m_iQpConverge;


int
m_iAdjustStepSize;


int
m_iMbAvgDistortion;


int
m_iPicEstActualQp;








static const int
m_iQpActualToSyntaxTable[365];







#else // _SRC_MB_INT—









double
m_dQpScale;
// Qp scalor to converge MbQp to PicQp









double
m_dQpConverge;
// converge speed


double
m_dAdjustStepSize;
// QpStep granularity


double
m_dMbAvgDistortion;
// Average distortion


double
m_dPicEstActualQp;
// Estimated Actual Pic Qp







#endif//_SRC_MB_INT—









2.2 Member Functions
The following are examples of the member functions employed in the present invention:

    int iecInit(JvtRcParameter*pRcParameter, JvtEtcParameter*pEtcParameter);
    int iRateCtrlMbBootUp(JvtRcParameter*pRcParameter, JvtPicParam*pJvtPicParam, int iOverheadBits);
    int iRateCtrlMbCalcComplexitylonly(int iMbNum, JvtPicParam*pPicParam, int iIntraAd);
    int iRateCtrlMbCalcQp(int iMbNum, JvtMbParam*pMbParam, int iIntraAd, int iInterAd);
    int iRateCtrlMbUpdate(int iMbNum, JvtMbParam*pMbParam, int iPicActBit);
    Int iRateCtrlMbAfter( );


3. MB-RC Implementation
Various parameters and functions associated with the methodology of the present invention are described as follows:
3.1 MB-RC iecInit
The member function ienInit(JvtRcParameter*pRcParameter, JvtEtcParameter*pEtcParameter) creates a working memory, and initializes slice-wide variables including: m_iMB_h, m_iMB_v, m_iNumOfMb and m_iQpConverge.
3.2 MB-RC Boot Up
The member function iRateCtrlMbBootUp(int iRetryCount, JvtPicParam*pJvtPicParam, int iOverheadBits) is called before encoding a slice in JvtSliceEncoding before the MB-coding loop. This function generally performs content complexity analysis and initializes slice-wide variables. Note that iRetryCount indicates the number of occurrences of re-encoding the current slice due to the VBV underflow. Normally it comprises a zero value.
The MB-RC Boot Up process proceeds according to the following steps.
Step 1: Calculate the MAD of each MB, comprising 4 blocks, as a basis for content complexity estimation, from the following:
MbMad=(MAD of the original source frame) per pixel




  
    (
    int
    )
  
  ⁢
  
    (
    
      
        (
        
          
            ∑
            
              i
              =
              0
            
            
              i
              =
              3
            
          
          ⁢
          
            
              ∑
              
                j
                =
                0
              
              
                j
                =
                63
              
            
            ⁢
            
              
              
                
                  X
                  
                    i
                    ,
                    j
                  
                
                -
                
                  
                    X
                    _
                  
                  i
                
              
              
            
          
        
        )
      
      /
      256.0
    
    )
  




where Xi,j denotes the pixel value at position j at block i, and Xi denote the mean value of the block i.
Step 2: Calculate the average MAD of the entire frame or slice from the following:




  MbAvgMad
  =
  
    (
    
      
        {
        
          
            ∑
            
              n
              =
              0
            
            
              n
              =
              k
            
          
          ⁢
          
            [
            
              
                (
                int
                )
              
              ⁢
              
                (
                
                  
                    (
                    
                      
                        ∑
                        
                          i
                          =
                          0
                        
                        
                          i
                          =
                          3
                        
                      
                      ⁢
                      
                        
                          ∑
                          
                            j
                            =
                            0
                          
                          
                            j
                            =
                            63
                          
                        
                        ⁢
                        
                          
                          
                            
                              X
                              
                                i
                                ,
                                j
                              
                            
                            -
                            
                              
                                X
                                _
                              
                              i
                            
                          
                          
                        
                      
                    
                    )
                  
                  /
                  256.0
                
                )
              
            
            ]
          
        
        }
      
      /
      k
    
    )
  




where k is the total number of MBs.

Step 3: Determine the intensity base of the entire frame/slice as follows:

IntensityBase=(MbAvgMad+1)/2

where IntensityBase is used as a bias to avoid large variation of intensity due to small MAD values.
Step 4: Determine the Qp dynamic range (i.e., LocalAdjRange) of the entire frame/slice as follows:

LocalAdjRange=min ((51-SyntaxQp)*(SyntaxQp+200)/6400.0, MAX_RANGE),

wherein MAX_RANGE=0.3 in this implementation. Certainly this number is controllable, depending on the scene content of a sequence. This value can be changed either in sequence base or in frame base. The larger its value is, the broader the Qp dynamic range is. If MAX_RANGE=0.0, then the Qp of the underlying picture level is used.
3.3 MB-RC Qp Calculation
3.3.1 I-Slice Coding
For I-slice:
iRateCtrlMbCalcComplexityIonly(int iMbNum, JvtPicParam*pPicParam, int iIntraAd)
Step 1: Obtain iMbIntraAdCur from Mode decision module and divide IntraAd by 256 for per pixel basis.
Step 2: Calculate various intensities. Here, two separate cases are considered: Case 1 is to encode the first I-frame where there is no average Ad and distortion information is available except the retrying encoding (then average Ad and distortion information is available, and Case 2 can be applied). Case 2 is a regular I-frame, which is inserted in every certain pre-specified interval.
Case 1: Scene Change I Slice or the First I Slice given no retry encoding:

MadIntensity=(MbMad[iMbNum]+1)/(MbAvgMad+1);

AdIntensity=(MbInterAdCur+1)/(EstMbAvgAd+1);

Where EstMbAvgAd=(m_iMbAvgMad+1)/MAD_DIV_AD_PER_PIXEL, and MAD_DIV_AD_PER_PIXEL=1.5 in this implementation based on the empirical values in Tables 4 and 5 which show the MAD and AD value in the selected sequences, and their relation.
Next, the index is calculated, T1, representing coding (i.e., Ad) activity, and limit T1 in +/− LocalAdjRange that is calculated in step 4 of section 3.2 to avoid large fluctuations.

T1=MadIntensity/AdIntensity

These indexes provide a measure of the intensity of Mad versus Ad.
The basic empirical observation is to assume that if T1 equals to 1, meaning that Ad and Mad both are in average level, the Qp level should be kept at the Pic target Qp. If T1 is greater than 1, meaning the content of this MB is pretty busy (above average), its coding complexity (AD) is below average, so its QP will be increased due to its high complex content. On the other hand, if T1 is smaller than 1, then Qp will be decreased due to its “easy”, or flat content.















If (MadIntensity <= 1.0) {









T1 = MIN(T1, MadIntensity)









}



else {









T1 = MAX(T1, MadIntensity)









}










To weigh the content complexity of a MB, we also add the above MIN and MAX operations to ensure the MB is properly interpreted.
Then limiting IntraLocalAdj:
//coding intensity
IntraLocalAdj=limit(1-LocalAdjRange, T1, 1+LocalAdjRange);
Case 2: Regular I-Frame(Slice). In addition to the above similar calculations for Case 1, an additional index T2 is needed. The new intensity calculations are listed below:

DistIntensity=(MbDistortionMap[iMbNum]+IntensityBase)/(MbAvgDistortion+IntensityBase)

MadIntensity=(MbMad[iMb]+IntensityBase)/(MbAvgMad+IntensityBase)

AdIntensity=(MbInterAdCur+IntensityBase)/(MbAvgAd+IntensityBase);

where IntensityBase is derived in step 3 of section 3.2.

Next, indices, T1, and T2, are calculated which represent coding (i.e., Ad) activity and Distortion versus Mad, and limit T1 and T2 in +/− LocalAdjRange calculated in step 4 of section 3.2 to avoid large fluctuations.

T1=MadIntensity/AdIntensity

T2=MadIntensity/DistIntensity

Then,
















If (MadIntensity <= 1.0) {









T1 = MIN(T1, MadIntensity)



T2 = MIN(T2, MadIntensity)









}



else {









T1 = MAX(T1, MadIntensity)



T2 = MAX(T2, MadIntensity)









}










Then limiting T1 and T2:
//coding intensity
T1=limit(1-LocalAdjRange, T1, 1+LocalAdjRange);
//distortion intensity
T2=limit(1-LocalAdjRange, T2, 1+LocalAdjRange);
Next, combining both indexes into one by weighting each index as:

IntraLocalAdj=X*T1+(1.0−X)*T2

    
    
        wherein X is an empirical value, and can be controlled by the application, such as given by X=0.5 in this implementation.
    
    


From this point, both cases execute the following steps.
Step 3: determine the QpStep granularity as:

IntraLocalAdjust=(IntraLocalAdjust−1.0)*AdjustStepSize.

Note that AdjustStepSize is decided by the content complexity of the current MB. AdjustStepSize is a key factor to determine the range of Qp dynamic changes and is derived as:
dAdjustStepSize=(iMbQpGap-m_iPicEstSyntaxQp)*0.01 and
iMbQpGap=200 if m_piMbMad[iMbNum]<m_iMbAvgMad;

    
    
        =80 if (m_piMbMad[iMbNum]>m_iMbAvgMad)
        =130 otherwise.
    
    


Note that these numbers (200, 80 and 130) are empirical numbers, and can be modified as needed. The value m_iMbAvgMad is the average Mad per pixel and m_piMbMad[iMbNum] is the Mad value per pixel of the current MB, iMbNum. The detail is described in section 3.2. It should be appreciated that as the value of AdjustStepSize increases, the Qp dynamic range increases.
Step 4: IntraLocalAdjust is offset by the average local adjust of its previous slice(frame) in order to be closer to the target picture Qp.

IntraLocalAdj−=AvgLocalAdj

Step 5: calculate the first actual Qp=m_dPicEstActualQp*(1+IntraLocalAdj)
Step 6: convert to the syntax m_iMbQpCur from (int)(6* log(Qp)/ log(2)+0.5).
Step 7: smooth iMbQpCur using a simple linear filter
m_iMbQpCur=(int)(m_iMbQpPrv*SRC_MB_PRVMB_EFFECT+m_iMbQpCur*(1.0-SRC_MB_PRVMB_EFFECT))
where iMbQpPrv is the syntax Qp of the previous MB, and SRC_MB_PRVMB_EFFECT is the weighting factor of the previous MB. In this implementation, its value is 0.2.
Step 8: finally the iMbQpCur is capped between SRC_MB_MIN_SYTAX_QP and SRC_MB_MAX_SYNTAX_QP.
3.3.2 P-Slice Coding
For P-slice and B-slice:
iRateCtrlMbCalcQp(intiMbNum, JvtMbParam*pMbParam, int I IntraAd, int iInterAd)
The following discussion is for a inter macro-block only. For a inter macro-block, all of the execution steps are very similar, except changing Inter MB to Intra MB.
Step 1: Obtain IntraAd and InterAd from Mode decision module and divide IntraAd and InterAd by 256 for per pixel basis.
Step 2: Calculate Distortion, Mad and Ad intensity as follows:

DistIntensity=(MbDistortionMap[iMbNum]+IntensityBase)/(MbAvgDistortion+IntensityBase)

MadIntensity=(MbMad[iMbNum]+IntensityBase)/(MbAvgMad+IntensityBase)

AdIntensity=(MbInterAdCur+IntensityBase)/(MbAvgAd+IntensityBase)

Note that the DistortionMap and its average is derived from its previous frame (slice) since we assume that the content activity between two successive frames (except scene cut) is very similar in co-location MB. And the AvgAd is obtained from its previous frame (slice) too.
Step 3: Calculate two indexes, T1 and T2, representing coding (i.e., Ad) and content (i.e., Distortion) activities, and limit T1 and T2 in +/− LocalAdjRange in section 3.2 to avoid large fluctuations, where its maximum value is 0.3 in this example. If LocalAdjRange=0.0, then the picture level Qp is used.

T1=MadIntensity/AdIntensity

T2=MadIntensity/DistIntensity

These indexes provide a measure of the intensity of Mad versus Ad, and distortion. The basic empirical observation is to assume that if T1 equals to 1, meaning that Ad and Mad both are in average level, the Qp level should be kept at the Pic target Qp. If T1 is large than 1, meaning the content of this MB is pretty busy (above average), its coding complexity (AD) is below average, so its QP will be increased due to its high complex content. On the other hand, if T1 is smaller than 1, then Qp will be decreased due to its “easy”, or flat content.















If (MadIntensity <= 1.0) {









T1 = MIN(T1, MadIntensity)



T2 = MIN(T2, MadIntensity)









}



else {









T1 = MAX(T1, MadIntensity)



T2 = MAX(T2, MadIntensity)









}










To weigh the content complexity of a MB, we also add the above MIN and MAX operations to ensure the MB is properly interpreted.
Step 4: combine both indexes into one by weighting each index as:

InterLocalAdjust=X*T1+(1.0−X)*T2

wherein X is an empirical value, and can be controlled by the application, such as given by X=0.5 in this implementation.

Step 5: determine the QpStep granularity as

(InterLocalAdjust−1.0)*AdjustStepSize.

Next we decide the Qp directions (increasing/decreasing) depending on the result of step 5. If it is less than 1, then Qp will be decreased by (InterLocalAdjust−1.0) times AdjustStepSize. AdjustStepSize is a key factor to determine the range of Qp dynamic changes and is derived as:
dAdjustStepSize=(iMbQpGap-m_iPicEstSyntaxQp)*0.01 and
iMbQpGap=200 if m_piMbMad[iMbNum]<m_iMbAvgMad;

    
    
        =80 if (m_piMbMad[iMbNum]>m_iMbAvgMad)
        =130 otherwise.
    
    


Note that these numbers (200, 80 and 130) are empirical values, and can be modified as needed. The value m_iMbAvgMad is the average Mad per pixel and m_piMbMad[iMbNum] is the Mad value per pixel of the current MB, iMbNum. The detail is described in section 3.2. The larger the value of AdjustStepSize, the greater the Qp dynamic range.
Step 6: InterLocalAdjust is offset by the average local adjust of its previous slice(frame) in order to be closer to the target picture Qp.

IntraLocalAdj−=AvgLocalAdj

Step 7: calculate the first actual Qp=m_dPicEstActualQp*(1+dIntraLocalAdj)
Step 8: convert to the syntax m_iMbQpCur from (int)(6* log(Qp)/ log(2)+0.5)
Step 9: smooth iMbQpCur using a simple linear filter
m_iMbQpCur=(int)(m_iMbQpPrv*SRC_MB_PRVMB_EFFECT+m_iMbQpCur*(1.0-SRC_MB_PRVMB_EFFECT)),
where iMbQpPrv is the syntax Qp of the previous MB, and SRC_MB_PRVMB_EFFECT is the weighting factor of the previous MB. In this example, its value is 0.2.
Step 10: finally the iMbQpCur is capped between

    
    
        SRC_MB_MIN_SYTAX_QP and SRC_MB_MAX_SYNTAX_QP.
    
    


3.4 MB-RC Update
iRateCtrlMbUpdate(int iMbNum, JvtMbParam*pMbParam, int iPicActBit)
This function provides for collecting the actual AD (depending on MB-type), Qp, and determining the QpScale value for the next MB coding.
3.5 MB-RC Clean UP
iRateCtrlMbAfter( )
This function is to calculate the distortion of a MB, and sum up for a frame. It also calculates the average Ad of a frame. The MB distortion is its Sum of Absolute Difference (SAD).
4. Details of MB Rate Control Steps
4.1 MB Rate Control Execution Flow and Data Flow
Referring again to FIG. 6, the execution flow and data flow according to an embodiment of the invention is illustrated as follows.
Block 100 illustrates the ienInit step which comprises the following:
(a) initialize data members;
(b) set image dimension information is set; and
(c) allocate working memory.
Block 102 illustrates the iRateCtrlMbBootUp step which comprises the following:

    
    
        (a) Obtain the picture level target Qp from picture level rate control;
        (b) Calculate each MB content complexity (MbMad) and average Mad;
        (c) Determine intensity base; and
        (d) Determine local adjust range.
    
    


Block 104 illustrates the Mode Decision step which comprises calculating InterAD and IntraAD. If the steps at blocks 106 and 108 have already been executed, the mode decision module determines the final mode and its Qp.
Block 106 illustrates the iRateCtrlMbCalcComplexityIonly step which comprises the following:
(a) Obtain IntraAd from mode decision module;
(b) Calculate MB-level Qp in I-slice; and
(c) Send this Qp back to mode decision module.
Block 108 illustrates the iRateCtrlMbCalcQp which comprises the following:

    
    
        (a) Obtain IntraAd and InterAd from mode decision module;
        (b) Calculate two MB-level Qps, IntraQp and InterQp, for Inter mode and Intra mode, respectively in P-slice; and
        (c) Send back these two Qps to mode decision module.
    
    


Block 110 illustrates the iecMbCoding step which comprises encoding the current MB.
Block 112 illustrates the vRateCtrlMbUpdate step which comprises the following:
(a) Accumulate Qp, Ad and the number of coded MBs; and
(b) If no mode MB coding, jump to block 104, else go to block 114.
Block 114 illustrates the vRateCtrlMbAfter step which comprises the following:
(a) Calculate the distortion of the current frame;
(b) Calculate the average Ad for the next frame; and
(c) Calculate the average LocalAdj for the next frame.
4.2 Content Complexity Representation
Content complexity analysis, per MB Mad calculation and its average value, is performed before the first MB of a slice is encoded. The calculation of per MB Mad and its average is shown below.

    
    
        (a) Calculating the MAD of each MB, comprising 4 blocks, as a basis for content complexity estimation.

MbMad=(MAD of the original source frame) per pixel

    
    






  
    (
    int
    )
  
  ⁢
  
    (
    
      
        (
        
          
            ∑
            
              i
              =
              0
            
            
              i
              =
              3
            
          
          ⁢
          
            
              ∑
              
                j
                =
                0
              
              
                j
                =
                63
              
            
            ⁢
            
              
              
                
                  X
                  
                    i
                    ,
                    j
                  
                
                -
                
                  
                    X
                    _
                  
                  i
                
              
              
            
          
        
        )
      
      /
      256.0
    
    )
  




Wherein Xi,j denotes the pixel value at position j at block i, and Xi denote the mean value of the block i.

    
    
        (b) Calculating the average MAD of the entire frame or slice:
    
    






  MbAvgMad
  =
  
    (
    
      
        {
        
          
            ∑
            
              n
              =
              0
            
            
              n
              =
              k
            
          
          ⁢
          
            [
            
              
                (
                int
                )
              
              ⁢
              
                (
                
                  
                    (
                    
                      
                        ∑
                        
                          i
                          =
                          0
                        
                        
                          i
                          =
                          3
                        
                      
                      ⁢
                      
                        
                          ∑
                          
                            j
                            =
                            0
                          
                          
                            j
                            =
                            63
                          
                        
                        ⁢
                        
                          
                          
                            
                              X
                              
                                i
                                ,
                                j
                              
                            
                            -
                            
                              
                                X
                                _
                              
                              i
                            
                          
                          
                        
                      
                    
                    )
                  
                  /
                  256.0
                
                )
              
            
            ]
          
        
        }
      
      /
      k
    
    )
  




Wherein k is the total number of MBs.
4.3 Intensity Based Qp Adiustment
The present invention further comprises a new intensity based approach to derive the Qp value for each MB. The intensity is defined as (current_value)/(average_value). In this implementation, three different intensities are used; namely Mean Absolute Difference (MAD) intensity, Absolute Difference (AD) intensity, and Distortion intensity. Furthermore, to reduce the “noise” effect on this calculation, an intensity base is added, which is used to reduce this effect to avoid large Qp fluctuation. In this implementation, the intensity based is defined as (average MAD)/2.
The three intensities according to the present invention are defined as:

DistIntensity=(MbDistortionMap[iMbNum]+IntensityBase)/(MbAvgDistortion+IntensityBase)

MadIntensity=(MbMad[iMbNum]+IntensityBase)/(MbAvgMad+IntensityBase)

AdIntensity=(MbInterAdCur+IntensityBase)/(MbAvgAd+IntensityBase);

Note that the MAD and AD calculations were previously defined at paragraph[0084]. Basically MAD intensity denotes content complexity, and AD denotes the coding complexity since it is obtained from motion estimation module. Distortion intensity provides compensation for the coding artifact.
Then two indices, T1 and T2, are introduced to measure the relative intensity, as shown below

T1=MadIntensity/AdIntensity

T2=MadIntensity/DistIntensity

Generally speaking, smaller T1 and T2 shall derive smaller Qp, resulting in better quality. The basic empirical observation is to assume that if T1 equals to 1, meaning that Ad and Mad both are in average level, Qp level should be kept at the Pic target Qp. If T1 is greater than 1, meaning the content of this MB is pretty busy (above average), but its coding complexity (AD) is below average, its QP will be increased due to its high complexity content. On the other hand, if T1 is smaller than 1, then Qp will be decreased due to its “easy”, or flat content.
To further differentiate the content of a MB, a simple maximum and minimum operation can be used to select the larger value or smaller value, respectively.















If (MadIntensity <= 1.0) {









T1 = MIN(T1, MadIntensity)



T2 = MIN(T2, MadIntensity)









}



else {









T1 = MAX(T1, MadIntensity)



T2 = MAX(T2, MadIntensity)









}










For example, if two macro-blocks (M1, and M2) both have the same T1(M1)=T1(M2)=1.0, but MadIntensity(M1)=2.0 and MadIntensity(M2)=1.0. Then without this MIN and MAX operation, both will have the same T1 value. However, with this operation, T1(M1)=1.0, but T1(M2) becomes 2.0, resulting in higher Qp. This result is expected since any noise in higher content complexity is less sensitive to this vision system.
Finally, T1 and T2 are limited in +/− LocalAdjRange range, where LocalAdjRangew will be explained in section [00161].

T1=limit(1-LocalAdjRange, T1, 1+LocalAdjRange);

T2=limit(1-LocalAdjRange, T2, 1+LocalAdjRange)

Note that in the first I-frame(slice) and scene change I-frame(slice), the distortion information is not available before encoding a MB, then only T1 will be derived. Otherwise both T1 and T2 have to be calculated.
4.4 Adaptivelv Adiust Qp Range
LocalAdjRange is calculated as follows:
MIN ((51-SyntaxQp)*(SyntaxQp+200)/6400.0, MAX_RANGE) where MAX_RANGE=0.3 in this implementation. This LocalAdjRange is controllable, depending on the scene content of a sequence. This value can be changed either in sequence base or in frame base. The larger its value, the broader the Qp dynamic range. If MAX_RANGE=0.0, then the Qp of the underlying picture level is used. LocalAdjRange also shows that in the higher Qp in picture level, the dynamic range of Qp is narrowed, and its distribution versus SyntaxQp is depicted in FIG. 7.
4.5 Adaptively Adjust Qp Step Size
After determining T1 and T2 in section [00151], the next step is to determine the Qp adjustment, LocalAdj. The formula is as follows:

LocalAdj=limit (1-LocalAdjRange, AD_WEIGHT*T1+(1-AD_WEIGHT)*T2, 1+LocalAdjRange),

where LocalAdjRange is described in section [00161], and AD_WEIGHT is the fraction value in the range of 0.0 to 1.0. In our case, 0.5 is used to show that both T1 and T2 are equally important. LocalAdj is in the range of 1+/−LocalAdjRange. Smaller LocalAdj (i.e., <1.0) will have smaller Qp (i.e., <picture-level Qp).

Before going into the detailed discussion of “Adjust Qp Step size”, we review the process of Qp calculation.

Step 1: LocalAdj=(LocalAdj−1.0)*AdjustStepSize;

Step 2: LocalAdj=AvgLocalAdj;

Step 3: Qp=PicEstActualQp*(1+LocalAdj);

Step 1 is to transform the LocalAdj from the range of (1+/− LocalAdjRange) to (+/−LocalAdjRange)*AdjustStepSize. That is, LocalAdj will increase (i.e., positive) or decrease (i.e., negative) the Qp value because of Step 3. Step 2 is performed to compensate the discrepancy between picture level target Qp, and MB level actual Qp in the previous frame (slice). Ideally the sum of LocalAdj for all MBs in a frame (slice) should be 0.0, so any leftover of sum of LocalAdj will be propagated to the next frame (slice) to ensure overall its approximation of picture-level Qp and bit rate.
Now let's discuss AdjustStepSize in step 1. This variable is to determine the granularity of adjustment step size. Its implementation is described below:















if (MbMad[iMbNum] < MbAvgMad) {









MbQpGap = 200;









}



else if (MbMad[iMbNum] > MbAvgMad) {









MbQpGap = 80;









}



else {









MbQpGap = 130;









}



AdjustStepSize = (iMbQpGap−PicEstSyntaxQp)*0.01.










Note that this is just an example of calculation of AdjustStepSize. These numbers 200, 80 and 130 are empirical values, and can be modified according to different encoding environments. The basic idea of this method is to control the AdjustStepSize by changing the MbQpGap based on its content complexity. This implementation says that if the content of current MB, (i.e., MbMad[iMbNUM]), is less than average complexity (MbAvgMad), then we can enlarge the MbQpGap value to significantly improve the perceptual quality in this smooth area. On the other hand, if it is larger than average complexity, a narrower MbQpGap is used to preserve the quality of this complex area. Flat areas show bigger MbQpGap values, resulting in significant improvement in visual quality, while in complex or busy areas, MbQpgap becomes small to preserve the quality to some degree. Those MBs with a negative value will be assigned smaller Qp and those MBs with positive values will be assigned bigger Qp for step 3.
4.6 Approximation of Picture Level QP
In the MB algorithm of the present invention, there is no target bit information from picture level rate control. Instead, only the picture level target Qp is given to MB rate control. Therefore, to properly control the bit rate (to make both of them generate around the same bits in picture level and sequence level), the MB rate control is trying to get the average Qp, which is about the same value as PIC rate control. The way the MB rate control does this is to calculate the average Qp, and also calculate the average LocalAdj to realize that if the current local adjustment is too light or too overdosing, then the leftover part will be propagated to the next frame. For example, if the average LocalAdjust is −0.22, meaning that in this frame, most of the MBs will have smaller Qp than picture level Qp, then in the next frame, we have to compensate it by passing this information to the next frame. Thus, when MB rate control calculates the local adjust for the next frame, this leftover part will be taken into account in step 2 of section [00163].
5. Experimental Results
5.1 Target Bit rate Coding
Tables 6 and 7 illustrate the performance of the macroblock rate control algorithm described above versus picture level rate control. Table 6 shows the performance of MB rate control, while Table 7 shows the performance of picture level rate control.
The first column in both tables shows the coding condition of a bitstream. It is specified as follows, for example,

    
    
        bicy—1000K—30 F_G2_D31_Db1_ep0

where bicy: sequence name, 1000K: target bit rate is 1000 Kbits per second, 30 F: target frame rate is 30 frames per second, G2: insert I-frame is every two seconds, D31: delay is 31 frames, Db1: deblocking filter is enabled, ep0: CAVLC entropy coding is used. The second column in both tables shows the dimension of the image and its scan mode: i denotes interlaced source video, and p denotes progressive source video. The third column (R) shows the actual bit rate. The third column (I-Qp) shows average Qp for I frames. The fourth column (P-Qp) shows the average Qp for P frames. The seventh to ninth columns show the average PSNR values.

    
    


In this experiment, MbRc was slightly worse in terms of PSNR value, but in terms of visual quality, it demonstrated a significantly superior visual quality due to its intensity based bit distribution. The basic idea is to lower Qp value to significantly improve the flat and smooth area, to which the human visual system is quite sensitive, while it increases Qp value in busy and complex areas (insensitive to the vision system) to improve the overall bit rate and quality.
5.2 FixQP Coding
Table 8 shows all the frame coding information including Qp, Bits and PSNR for picture level rate control and MB level rate control in encoding a sample sequence using Qp=35. The last row summarizes the results that picture level rate control spends 50107 bits on average per frame, while the MB rate control of the present invention spends 42365 bits per frame and its average Qp=34.66. The PSNR value is around 1.0 db difference. But in terms of the visual quality, again the MB rate control shows around the same or better quality than picture level rate control.
Although the description above contains many details, these should not be construed as limiting the scope of the invention but as merely providing illustrations of some of the presently preferred embodiments of this invention. Therefore, it will be appreciated that the scope of the present invention fully encompasses other embodiments which may become obvious to those skilled in the art, and that the scope of the present invention is accordingly to be limited by nothing other than the appended claims, in which reference to an element in the singular is not intended to mean “one and only one” unless explicitly so stated, but rather “one or more.” All structural and functional equivalents to the elements of the above-described preferred embodiment that are known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the present claims. Moreover, it is not necessary for a device or method to address each and every problem sought to be solved by the present invention, for it to be encompassed by the present claims. Furthermore, no element, component, or method step in the present disclosure is intended to be dedicated to the public regardless of whether the element, component, or method step is explicitly recited in the claims. No claim element herein is to be construed under the provisions of 35 U.S.C. 112, sixth paragraph, unless the element is expressly recited using the phrase “means for.”







TABLE 1







iNumberOfMB = (iHSize/iYMBHSize) * (iVSize/iYMBVSize);


dBit rateForABlock = (m_pEnc −> m_iBit rate)/(iNumberOfMB)


dFrameRate


















Bits
Bits




bit



per
per

New


rate
framerate
width
height
MB
pixel
Ratio
MinQP

















10000
5
176
144
20.20
0.08
101.38
5


10000
7.5
176
144
13.47
0.05
152.06
6


10000
10
176
144
10.10
0.04
202.75
6


10000
15
176
144
6.73
0.03
304.13
8


10000
30
176
144
3.37
0.01
608.26
8


32000
10
176
144
32.32
0.13
63.36
4


32000
15
176
144
21.55
0.08
95.04
5


32000
30
176
144
10.77
0.04
190.08
6


64000
10
176
144
64.65
0.25
31.68
3


64000
15
176
144
43.10
0.17
47.52
3


64000
30
176
144
21.55
0.08
95.04
5


192000
10
352
288
48.48
0.19
42.24
3


192000
15
352
288
32.32
0.13
63.36
4


192000
30
352
288
16.16
0.06
126.72
6


256000
10
352
288
64.65
0.25
31.68
3


256000
15
352
288
43.10
0.17
47.52
3


256000
30
352
288
21.55
0.08
95.04
5


384000
10
352
288
96.97
0.38
21.12
1


384000
15
352
288
64.65
0.25
31.68
3


384000
30
352
288
32.32
0.13
63.36
4


1500000
30
1208
1152
9.20
0.04
222.66
8


2000000
30
1208
1152
12.26
0.05
166.99
6


4000000
30
1208
1152
24.53
0.10
83.50
5


6000000
30
1208
1152
36.79
0.14
55.66
4


8000000
30
1208
1152
49.06
0.19
41.75
3
















TABLE 2







Positive part


(I.e., buffer could be overflow)
















Prv
Tar


Final
Prv
Tar


Final


QP
QP
Dev*
1-Dev
QP
QP
QP
Dev*
1-Dev
QP



















28
8
0
1
18
3
8
0
1
8


28
8
0.1
0.9
18
3
8
0.1
0.9
7.05


28
8
0.2
0.8
18
3
8
0.2
0.8
6.2


28
8
0.3
0.7
17.8
3
8
0.3
0.7
5.45


28
8
0.4
0.6
15.2
3
8
0.4
0.6
4.8


28
8
0.5
0.5
13
3
8
0.5
0.5
4.25


28
8
0.6
0.4
11.2
3
8
0.6
0.4
3.8


28
8
0.7
0.3
9.8
3
8
0.7
0.3
3.45


28
8
0.8
0.2
8.8
3
8
0.8
0.2
3.2


28
8
0.9
0.1
8.2
3
8
0.9
0.1
3.05


28
8
1
0
8
3
8
1
0
3























TABLE 3





Prv
Tar

Final
Prv
Cur

Final


QP
QP
Dev**
QP
QP
QP
Dev**
QP






















28
8
0
8
3
8
0
3


28
8
0.1
8.2
3
8
0.1
3.05


28
8
0.2
8.8
3
8
0.2
3.2


28
8
0.3
9.8
3
8
0.3
3.45


28
8
0.4
11.2
3
8
0.4
3.8


28
8
0.5
13
3
8
0.5
4.25


28
8
0.6
15.2
3
8
0.6
4.8


28
8
0.7
17.8
3
8
0.7
5.45


28
8
0.8
20.8
3
8
0.8
6.2


28
8
0.9
24.2
3
8
0.9
7.05


28
8
1
28
3
8
1
8




















TABLE 4





SD
Bit rate
MAD per pixel
AD per pixel
MAD/AD



















bicycle
1000K
12.67
9.64
1.31


Bus
1000K
13.23
9.27
1.43


Car
1000K
11.28
8.21
1.37


cheer
1000K
12.53
8.68
1.44


confe
1000K
10.74
7.19
1.49


football
1000K
8.70
6.32
1.38


flower
1000K
14.84
11.32
1.31


marble
1000K
12.41
4.42
2.81


mobile
1000K
17.39
13.35
1.30


Pop
1000K
8.57
6.75
1.27


tennis
1000K
15.73
14.51
1.08


Face
1000K
2.82
0.79
3.57



1000K
3.24
1.75
1.85



1000K
3.54
2.22
1.59


Wall
1000K
1.69
1.02
1.66



1000K
3.03
1.59
1.91



1000K
2.03
1.38
1.47


battle
1000K
2.77
2.23
1.24



1000K
3.77
3.74
1.01



1000K
5.45
3.99
1.37










AVERAGE
8.32
5.92
1.59




















TABLE 5





SIF/CIF
Bit rate
MAD per pixel
AD per pixel
MAD/AD



















bicycle
384K
12.38
9.20
1.35


cheer
384K
15.07
11.82
1.27


child
384K
9.04
5.60
1.61


foreman
384K
6.68
3.50
1.91


fountain
384K
14.21
11.98
1.19


mino
384K
8.76
4.98
1.76


mobile
384K
18.76
13.94
1.35


new2
384K
7.70
4.84
1.59


papa
384K
3.79
2.57
1.47










AVERAGE
10.71
7.60
1.50























TABLE 6





Bistream (MB)
Dimension
Bit rate
I-Qp
P-Qp
PSNR-Y
PSNY-Cb
PSNR-Cr







bicy_1000K_30F_G2_D31_Db1 _ep0
720 × 480i
1040.0K 
42.28
43.00
23.24
33.75
32.76


bus_1000K_30F_G2_D31_Db1_ep0
720 × 480i
953.4K
38.65
39.26
25.66
37.40
35.60


cheer_1000K_30F_G2_D31_Db1_ep0
720 × 480i
1053.7K 
43.77
45.17
21.90
30.17
29.27


child_384K_30F_G2_D31_Db1_ep0
352 × 288p
379.1K
32.43
33.67
31.62
33.93
33.63


flower_1000K_30F_G2_D31_Db1_ep0
720 × 480i
985.5K
39.44
40.54
22.91
32.18
30.92


foreman_384K_30F_G2_D31_Db1_ep0
352 × 288p
385.9K
28.32
29.72
33.92
41.20
39.67


foundtain_1000K_30F_G2_D31_Db1_ep0
320 × 240p
1184.1K 
32.76
35.54
26.47
44.12
43.35


mino_384K_30F_G2_D31_Db1_ep0
320 × 240p
342.2K
26.60
27.85
35.17
38.88
37.08


news2_384K_30F_G2_D31_Db1_ep0
320 × 240p
418.8K
28.30
30.29
34.26
39.24
37.74


papa_384K_30F_G2_D31_Db1_ep0
320 × 240p
380.8K
22.87
23.63
39.76
44.02
42.87


pop_1000K_30F_G2_D31_Db1_ep0
720 × 480i
1168.4K 
37.40
38.86
27.55
32.52
32.07


sasam_384K_30F_G2_D31_Db1_ep0
320 × 240p
370.4K
25.63
26.35
36.60
43.09
43.13























TABLE 7





Bistream (PIC)
Dimension
Bit rate
I-Qp
P-Qp
PSNR-Y
PSNY-Cb
PSNR-Cr







bicy_1000K_30F_G2_D31_Db1_ep0
720 × 480i
1047.7K 
43.67
43.48
23.63
33.69
32.69


bus_1000K_30F_G2_D31_Db1_ep0
720 × 480i
968.6K
41.00
40.32
25.76
37.25
35.51


cheer_1000K_30F_G2_D31_Db1_ep0
720 × 480i
1045.7K 
45.00
45.24
22.33
30.10
29.25


child_384K_30F_G2_D31_Db1_ep0
352 × 288p
382.7K
34.80
34.88
31.56
33.58
33.22


flower_1000K_30F_G2_D31_Db1_ep0
720 × 480i
996.3K
41.67
41.65
23.04
32.14
30.93


foreman_384K_30F_G2_D31_Db1_ep0
352 × 288p
389.3K
30.00
30.34
34.31
41.35
39.88


foundtain_1000K_30F_G2_D31_Db1_ep0
320 × 240p
1149.5K 
35.67
37.75
26.42
43.13
42.77


mino_384K_30F_G2_D31_Db1_ep0
320 × 240p
341.7K
28.17
28.27
35.61
38.95
37.21


news2_384K_30F_G2_D31_Db1_ep0
320 × 240p
418.4K
29.71
30.86
34.72
39.35
37.83


papa_384K_30F_G2_D31_Db1_ep0
320 × 240p
396.1K
24.33
24.27
40.32
44.36
43.16


pop_1000K_30F_G2_D31_Db1_ep0
720 × 480i
1174.5K 
40.33
40.51
27.77
32.19
31.81


sasam_384K_30F_G2_D31_Db1_ep0
320 × 240p
372.1K
27.44
27.55
37.02
43.13
43.09



















TABLE 8







Frame

PIC Rate Control
MB Rate Control














No.
Type:
PIC-QP
BITS
PSNR-Y
Avg-QP
BITS
PSNR-Y

















0
I:
35
72064
29.76
31.8
86728
30.75


1
P:
35
48128
28.26
34.9
39224
26.94


2
P:
35
54808
27.95
34.5
50200
27.24


3
P:
35
52120
28.04
34.7
43592
26.77


4
P:
35
54504
27.94
34.8
44464
26.53


5
P:
35
49088
28.18
34.8
41696
26.91


6
P:
35
48160
28.3
34.7
40232
26.95


7
P:
35
47560
28.37
34.7
40168
27.01


8
P:
35
48304
28.26
34.8
40336
26.84


9
P:
35
54048
27.97
34.8
45496
26.54


10
P:
35
48448
28.32
34.8
40104
26.88


11
P:
35
51904
28.06
34.8
42776
26.72


12
P:
35
50440
28.14
34.8
41512
26.68


13
P:
35
51600
28.07
34.7
43336
26.73


14
P:
35
50520
28.09
34.7
43264
26.77


15
P:
35
55576
27.99
34.7
47384
26.65


16
P:
35
54600
27.99
34.7
46464
26.62


17
P:
35
54080
28.03
34.8
44632
26.55


18
P:
35
51080
28.27
34.6
45528
27.38


19
P:
35
55472
28.06
34.4
49216
27.18


20
P:
35
54216
28.11
34.7
45600
26.65


21
P:
35
48784
28.37
34.8
40344
26.87


22
P:
35
54816
28.04
34.7
46272
26.62


23
P:
35
53664
28.17
34.7
44336
26.72


24
P:
35
50288
28.24
34.7
41840
26.79


25
P:
35
51480
28.18
34.6
43432
26.82


26
P:
35
49640
28.32
34.8
39184
26.83


27
P:
35
52608
28.12
34.6
44552
26.79


28
P:
35
53488
28.03
34.7
43968
26.59


29
P:
35
52712
28.07
34.7
43584
26.6


30
P:
35
48344
28.37
34.8
39024
26.89


31
P:
35
52712
28.09
34.7
43872
26.66


32
P:
35
54064
28.06
34.7
45344
26.61


33
P:
35
55904
27.95
34.7
46824
26.49


34
P:
35
55456
27.95
34.7
45744
26.52


35
P:
35
52984
28.17
34.6
44720
26.84


36
P:
35
55648
28
34.7
47792
26.66


37
P:
35
53176
28.13
34.8
43496
26.71


38
P:
35
48792
28.29
34.6
44072
27.54


39
P:
35
50712
28.2
34.4
45744
27.46


40
P:
35
49800
28.23
34.7
40728
26.84


41
P:
35
48720
28.23
34.8
40656
26.87


42
P:
35
52520
28.13
34.9
43376
26.63


43
P:
35
51504
28.16
34.6
46296
27.33


44
P:
35
52064
28.06
34.3
48688
27.32


45
P:
35
54720
27.99
34.8
45368
26.51


46
P:
35
56408
27.9
34.8
46288
26.44


47
P:
35
53488
28.09
34.7
43672
26.59


48
P:
35
51472
28.17
34.9
41136
26.64


49
P:
35
49984
28.2
34.5
45064
27.35


50
P:
35
57336
27.87
34.4
51760
27.08


51
P:
35
52688
28.04
34.8
43128
26.58


52
P:
35
55448
27.91
34.4
51328
27.16


53
P:
35
52560
28.05
34.7
44488
26.75


54
P:
35
50528
28.15
34.8
40880
26.71


55
P:
35
50672
28.11
34.8
42256
26.69


56
P:
35
51600
28.03
34.8
43112
26.68


57
P:
35
49392
28.27
34.7
40600
26.91


58
P:
35
50904
28.1
34.7
42208
26.73


59
P:
35
49520
28.25
34.7
41776
26.87


60
I:
35
69640
29.95
34.2
67336
29.36


61
P:
35
47624
28.43
34.7
38512
27.03


62
P:
35
55176
28.08
34.7
45880
26.66


63
P:
35
54592
27.94
34.8
45736
26.51


64
P:
35
54648
28.06
34.7
45520
26.62


65
P:
35
47424
28.31
34.7
40544
26.98


66
P:
35
51808
28.13
34.7
43704
26.73


67
P:
35
48824
28.34
34.7
40432
26.92


68
P:
35
47304
28.37
34.7
39488
27.04


69
P:
35
50104
28.17
34.7
41720
26.84


70
P:
35
52432
28.06
34.6
44232
26.79


71
P:
35
51136
28.16
34.6
42792
26.86


72
P:
35
47264
28.37
34.7
38992
27.04


73
P:
35
53824
27.99
34.7
45016
26.64


74
P:
35
48848
28.21
34.7
40096
26.85


75
P:
35
48584
28.17
34.7
40512
26.84


76
P:
35
46728
28.32
34.6
38592
27.01


77
P:
35
44840
28.35
34.8
37120
26.97


78
P:
35
48944
28.23
34.6
40856
26.89


79
P:
35
53432
28.03
34.6
44832
26.69


80
P:
35
48312
28.26
34.7
39584
26.87


81
P:
35
46616
28.4
34.7
38376
27.01


82
P:
35
50600
28.12
34.6
43272
26.89


83
P:
35
50024
28.21
34.7
40512
26.85


84
P:
35
47392
28.5
34.7
39512
27.11


85
P:
35
46360
28.49
34.7
38720
27.05


86
P:
35
48352
28.36
34.6
41544
27.02


87
P:
35
50528
28.24
34.6
42424
26.89


88
P:
35
46136
28.6
34.7
38520
27.22


89
P:
35
49152
28.26
34.7
41144
26.85


90
P:
35
46312
28.33
34.7
39008
27.04


91
P:
35
49544
28.2
34.6
41520
26.86


92
P:
35
47512
28.33
34.8
39152
27.02


93
P:
35
48984
28.24
34.4
45104
27.56


94
P:
35
44432
28.35
34.8
36384
27.07


95
P:
35
44448
28.39
34.8
36064
27.05


96
P:
35
49808
28.12
34.5
45320
27.37


97
P:
35
45480
28.29
34.9
37072
26.92


98
P:
35
45288
28.31
34.3
42568
27.65


99
P:
35
44216
28.41
34.8
36320
27.07


100
P:
35
45608
28.39
34.7
37176
27.07


101
P:
35
42000
28.53
34.8
34632
27.26


102
P:
35
43696
28.47
34.7
36056
27.2


103
P:
35
43576
28.48
34.8
35744
27.19


104
P:
35
46728
28.26
34.6
40728
27.04


105
P:
35
51568
28.13
34.8
42872
26.77


106
P:
35
48768
28.26
34.6
40656
26.96


107
P:
35
45248
28.39
34.8
36872
27


108
P:
35
50632
28.12
34.7
41840
26.76


109
P:
35
49232
28.2
34.7
41168
26.79


110
P:
35
44400
28.44
34.8
36200
27.07


111
P:
35
50552
28.05
34.6
43536
26.86


112
P:
35
47656
28.25
34.8
38744
27.01


113
P:
35
49376
28.23
34.5
42288
26.97


114
P:
35
50128
28.17
34.7
41208
26.82


115
P:
35
44864
28.43
34.7
36608
27.07


116
P:
35
44624
28.37
34.7
37024
27.02


117
P:
35
50968
28.19
34.7
41720
26.76


118
P:
35
49560
28.23
34.6
40960
26.93


119
P:
35
51400
28.11
34.7
42248
26.83


120
I:
35
68456
30.07
34.3
65816
29.38


121
P:
35
42520
28.66
34.7
34600
27.38


122
P:
35
45120
28.47
34.7
37208
27.12


123
P:
35
47280
28.34
34.6
39600
27.01


124
P:
35
47888
28.36
34.7
39208
26.95


125
P:
35
47648
28.43
34.8
38336
27


126
P:
35
43072
28.65
34.6
35672
27.3


127
P:
35
47944
28.35
34.6
40112
27.01


128
P:
35
45344
28.6
34.8
36200
27.12


129
P:
35
48384
28.37
34.5
41016
27.08


130
P:
35
45896
28.54
34.9
37816
27.09


131
P:
35
46952
28.39
34.8
38680
26.93


132
P:
35
43392
28.58
34.8
36432
27.2


133
P:
35
46656
28.35
34.6
38864
27.06


134
P:
35
48008
28.37
34.6
39216
26.97


135
P:
35
45600
28.46
34.8
36720
27.03


136
P:
35
52144
28.19
34.8
41680
26.75


137
P:
35
46648
28.44
34.8
37720
27.04


138
P:
35
46080
28.47
34.5
41136
27.67


139
P:
35
47568
28.36
34.3
42888
27.63


140
P:
35
50472
28.29
34.7
41416
26.79


141
P:
35
48800
28.31
34.6
41120
26.91


142
P:
35
53080
28.05
34.6
44920
26.71


143
P:
35
48016
28.41
34.9
40360
26.85


144
P:
35
47304
28.33
34.3
43240
27.62


145
P:
35
46072
28.44
34.9
37848
27.09


146
P:
35
47104
28.37
34.4
43440
27.71


147
P:
35
52144
28.1
34.6
43448
26.86


148
P:
35
52976
28.13
34.9
42920
26.64


149
P:
35
50848
28.22
34.5
45952
27.4




35
50107
28.26
34.66
42365
26.99

## Claims

1. A method for scalable macro block rate control in a video encoder having a processor and programming executable on the processor for carrying out the method, the method comprising:
performing an initialization step;
performing a boot up step comprising:
(i) obtaining a picture level target quantization parameter (QP) from a picture level rate control,
(ii) calculating, for each macro block (MB), content complexity and average mean absolute difference (MAD),
(iii) determining an intensity base for deriving the QP value for each macro block (MB), and
(iv) determining a local adjust range;

performing a mode decision step;
performing a complexity step;
calculating a quantization parameter (QP);
performing a coding step for encoding a current macro block;
performing a update step; and
performing an after update step.

2. A method as recited in claim 1, wherein said initialization step comprises:
initializing data members;
setting image dimension information; and
allocating working memory.

3. A method as recited in claim 1, wherein said step of mode decision comprises:
calculating InterAD and IntraAD values;
obtaining IntraAD values from a mode decision module;
calculating macro block level quantization parameter (QP) in I-slice; and
sending the macro block level QP to the mode decision module.

4. A method as recited in claim 1, wherein complexity step comprises:
obtaining IntraAd and InterAd from mode decision module;
calculating MB-level Qps, IntraQp and InterQp, for Inter mode and Intra mode, respectively in P-slice and B-slice;
sending said Qp values to the mode decision module.

5. A method as recited in claim 1, further comprising activating macro block rate control (MbRc) in response to enabling picture level rate control to pass the target quantization parameter (QP) of a frame to MbRc, prior to making a mode decision within the video encoder.

6. A method as recited in claim 1, wherein said update step comprises:
accumulating Qp, Ad and number of coded macroblocks.

7. A method as recited in claim 1, wherein said after update step comprises:
calculating distortion of a current frame;
calculating average Ad for a next frame; and
calculating average LocalAdj for the next frame.

8. A method of scalable macro block rate control in a video encoder having a processor and programming executable on the processor for carrying out the method, the method, comprising:
performing an initialization step;
performing a boot up step;
performing a mode decision step;
performing a complexity step;
calculating a quantization parameter (QP);
performing a coding step for encoding a current macro block;
performing an update step; and
performing an after update step comprising,
calculating distortion of a current frame,
calculating average Ad for a next frame, and
calculating average LocalAdj for the next frame.

9. A method as recited in claim 8, wherein said bootup step comprises:
obtaining a picture level target quantization parameter (QP) from a picture level rate control;
calculating, for each macro block (MB), content complexity and average mean absolute difference (MAD);
determining an intensity base for deriving the QP value for each macro block (MB); and
determining a local adjust range.

10. A method as recited in claim 8, wherein said step of mode decision comprises:
calculating InterAD and IntraAD values;
obtaining IntraAD values from a mode decision module;
calculating macro block level quantization parameter (QP) in I-slice; and
sending the macro block level QP to the mode decision module.

11. A method as recited in claim 8, wherein said complexity step comprises:
obtaining IntraAd and InterAd from mode decision module;
calculating macro block level Qps, IntraQp and InterQp, for Inter-mode and Intra-mode, respectively in P-slice and B-slice;
sending said Qp values to the mode decision module.

12. A method as recited in claim 8, wherein said update step comprises:
accumulating Qp, Ad and number of coded macro blocks.

13. A method as recited in claim 8, further comprising:
activating macro block rate control (MbRc) in response to enabling picture level rate control to pass the target quantization parameter (QP) of a frame to MbRc, prior to making a mode decision within the video encoder.

14. A method of performing macro block rate control (MbRc) in a video encoder having a processor and programming executable on the processor for carrying out the method, the method comprising:
activating macro block rate control (MbRc) in response to enabling picture level rate control to pass the target quantization parameter (QP) of a frame to MbRc;
calculating content complexity and average mean absolute difference (MAD) for each macro block;
determining an intensity base for deriving the QP value for each macro block (MB);
determining a local adjust range;
obtaining a picture level target QP from a picture level rate control within the video encoder;
executing a macro block coding loop within which a mode decision is made and the macro block is encoded; and
updating macro block rate control (MbRc).

15. A method as recited in claim 14, further comprising an after update step, executed after said updating of macro block rate control (MbRc), which comprises the steps of:
calculating distortion of a current frame;
calculating average Ad for a next frame; and
calculating average LocalAdj for the next frame.

16. A method as recited in claim 14, wherein said mode decision within the coding loop comprises:
calculating InterAD and IntraAD values;
obtaining IntraAD values from a mode decision module;
calculating macro block level quantization parameter (QP) in I-slice; and
sending the macro block level QP to the mode decision module.

17. A method as recited in claim 16, further comprising a complexity determination within said coding loop, which comprises the steps of:
obtaining IntraAd and InterAd from mode decision module;
calculating macro block-level Qps, IntraQp and InterQp, for Inter-mode and Intra-mode, respectively in P-slice and B-slice; and
sending said Qp values to the mode decision module.

18. A method of performing macro block rate control (MbRc) within a video encoder having a processor and programming executable on the processor for carrying out the method, the method comprising:
activating macro block rate control (MbRc) in response to enabling picture level rate control to pass the target quantization parameter (QP) of a frame to MbRc;
obtaining a picture level target QP from a picture level rate control within the video encoder;
executing a macro block coding loop within which a mode decision is made and the macro block is encoded;
calculating distortion of a current frame after the macro block coding loop;
calculating average Ad for a next frame; and
calculating average LocalAdj for the next frame.

19. A method as recited in claim 18, further comprising a bootup step, performed before said macro block coding loop, which comprises the steps of:
obtaining a picture level target quantization parameter (QP) from a picture level rate control;
calculating content complexity and average mean absolute difference (MAD) for each macro block;
determining an intensity base for deriving the QP value for each macro block (MB); and
determining a local adjust range.

20. A method as recited in claim 18, wherein said mode decision within the coding loop comprises:
calculating InterAD and IntraAD values;
obtaining IntraAD values from a mode decision module;
calculating macro block level quantization parameter (QP) in I-slice; and
sending the macro block level QP to the mode decision module.

21. A method as recited in claim 18, further comprising a complexity determination, within said coding loop, comprising:
obtaining IntraAd and InterAd from mode decision module;
calculating macro block-level Qps, IntraQp and InterQp, for Inter-mode and Intra-mode, respectively in P-slice and B-slice; and
sending said Qp values to the mode decision module.