RATE DISTORTION OPTIMIZATION FOR INTERPREDICTION IN H.264/AVC VIDEO CODING

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1 RATE DISTORTION OPTIMIZATION FOR INTERPREDICTION IN H.264/AVC VIDEO CODING Thesis Submitted to The School of Engineering of the UNIVERSITY OF DAYTON In Partial Fulfillment of the Requirements for The Degree of Master of Science in Electrical Engineering By Jonathan Patrick Skeans UNIVERSITY OF DAYTON Dayton, Ohio August, 2013

2 RATE DISTORTION OPTIMIZATION FOR INTERPREDICTION IN H.264/AVC VIDEO CODING Name: Skeans, Jonathan Patrick APPROVED BY: Eric Balster, Ph.D. Advisor Committee Chairman Assistant Professor, Department of Electrical and Computer Engineering Frank Scarpino, Ph.D. Committee Member Professor Emeritus, Department of Electrical and Computer Engineering Vijayan Asari, Ph.D. Committee Member Professor, Department of Electrical and Computer Engineering John G. Weber, Ph.D. Associate Dean School of Engineering Tony E. Saliba, Ph.D. Dean, School of Engineering & Wilke Distinguished Professor ii

3 ABSTRACT RATE DISTORTION OPTIMIZATION FOR INTERPREDICTION IN H.264/AVC VIDEO CODING Name: Skeans, Jonathan Patrick University of Dayton Advisor: Dr. Eric Balster Part 10 of MPEG-4 describes the Advanced Video Coding (AVC) method widely known as H.264. H.264 is the product of a collaborative effort known as the Joint Video Team (JVT). The final draft of the standard was completed in May of 2003 and since then H.264 has become one of the most commonly used formats for compression [1]. H.264, unlike previous standards, describes a myriad of coding options that involve variable block size inter prediction methods, nine different intra prediction modes, multi frame prediction and B frame prediction. There are a huge number of options for coding that will tend to generate a different number of coded bits and different reconstruction quality. A video encoder is challenged to minimize coded bitrate and maximize quality. However, choosing the coding mode of a macroblock to achieve this is a difficult problem due to the large number of coding combinations and parameters. Rate Distortion Optimization is an effective technique for choosing the best coding mode for a macroblock. This thesis presents two features of an H.264 encoder, multi frame prediction and B frame prediction. Additionally, a Rate Distortion Optimization scheme is implemented with the features to improve overall performance of the encoder. iii

4 For my friends and family iv

5 ACKNOWLEDGMENTS I would like to thank my family for their support during my time as a college student. I would also like to thank the following people for making the experience more rewarding: Thank you to Chris McGuinness for helping me learn H.264 and always being available to answer any questions I had. You have been an excellent role model, colleague, and friend. Thank you to the William Turri and the rest of the ADDA lab for all the assistance you have given me through out my time with UDRI. Thank you to Kerry Hill, Al Scarpelli, and the Air Force Research Laboratory for enabling the experience. Thank you to Dr. Frank Scarpino and Dr. Vijayan Asari for serving on my thesis committee. Thank you to Mike Ratterman and Chris Direnzi for putting up with me during undergrad. Special thanks to Dr. Eric Balster for taking a chance on me and serving as my advisor. v

6 TABLE OF CONTENTS ABSTRACT iii DEDICATION iv ACKNOWLEDGMENTS LIST OF FIGURES v viii LIST OF TABLES x I. Introduction Video Coding Overview Video Coding Standards H.264 Standard H.264 Overview Prediction Intra Prediction Inter Prediction Transform, Scaling, and Quantization Hadamard Transform Quantization Entropy Coding Exp-Golomb Coding CAVLC CABAC Profiles and Levels Mode Selection Rate Distortion Optimized Mode Selection Motivation and Organization vi

7 II. Multi Frame Prediction Interprediction Overview Syntax Overview Picture Ordering Reference Picture Lists Exp-Golomb Coding Motion Vector Prediction Multi Frame Encoding Conclusions III. B Frame Inter Prediction B Frame Inter Prediction Overview B Frame Reference Picture Lists B Frame Coding SPS and PPS Decoded Picture Buffer Create Search Window Block Match, Transform and Quantize Motion Vector Prediction B Frame Implementation B Frame Conclusions IV. Mode Selection Introduction Proposed Low Complexity RDO Method Proposed RDO Method Implementation Conclusions V. Conclusions and Future Work Conclusions Future Work BIBLIOGRAPHY vii

8 LIST OF FIGURES 1.1 Subdivision of Picture into Slices Prediction Samples for luma 4x4 prediction Macroblock Partitioning for Inter prediction Multiframe Motion Compensation Extracting DC Coefficients H.264 Syntax Layers H.264 Profiles Available Prediction Modes Macroblock Layer Overview: Baseline mb pred syntax overview sub mb pred syntax overview Display Order Example, Type Reference Picture Order Example: P Slices Current and neighboring partitions: 16x16 partitions Current and neighboring partitions: different partitions sizes Multi Frame Prediction Foreman viii

9 2.9 Multi Frame Prediction Flower Multi Frame Prediction Flyby Multi Frame Prediction Foreman Multi Frame Prediction Flower Complexity Multi Frame Prediction Flyby Complexity IPBB Display Order List0 and List1 Ordering Example B MB Prediction Block Diagram B MB Motion Vector Prediction Rate Distortion Curve Foreman using B Frame Interprediction Rate Distortion Curve Foreman using B Frame Interprediction for QPs 24 through Complexity using B Frame Interprediction Traditional RDO Proposed RDO Method Proposed RDO Results: Foreman Proposed RDO Complexity: Foreman Proposed RDO Results: Flower Proposed RDO Complexity: Foreman ix

10 LIST OF TABLES 1.1 Video Compression Standards Luma Prediction Modes, 4x4 prediction Exp-Golomb Codewords Mappings to codenum Display Order Example x

11 CHAPTER I Introduction 1.1 Video Coding Overview Digital media has gone through a significant change over the past 10 years [1]. Most consumers now receive digital television which offers a greater choice of channels, electronic guides, and high definition programming. DVDs and Blu-Ray Disks are the primacy medium for playing prerecorded movies and television programs. An alternative to this technology is Internet downloading and streaming. Many other changes in digital media include increased functionality of cellular telephones, increase in home internet speeds, and video calling via the internet. Many factors have contributed to the shift towards digital video including commercial factors, legislation, social changes and technological advances [1] One technical aspect that is key to the widespread adoption of digital video technology is video compression. Video compression is the process of reducing the amount of data required to represent a digital video signal, prior to transmission or storage [1]. The complementary operation, video decompression, recovers a digital signal from a compressed representation, prior to display. This entire process, known as video coding, is essential for any video application in which storage capacity or transmission bandwidth is limited. 1

12 1.2 Video Coding Standards Standards exist to simplify inter-operability between encoder and decoders from different manufactures. Table 1.1 shows a partial history of video compression standards. Table 1.1: Video Compression Standards Year Standard Publisher 1984 H.120 ITU-T 1988 H.261 ITU-T 1993 MPEG-1 Part 2 ISO, IEC 1995 H.262/MPEG-2 Part 2 ISO,IEC,ITU-T 1996 H.263 ITU-T 1999 MPEG-4 Part 2 ISO, IEC 2003 H.264/MPEG-4 AVC ISO,IEC,ITU-T 2013 H.265 ISO-Under development The requirements for a successful video coding standard include: interpretability: should assure that encoder and decoders from different manufactures work together seamlessly. Innovation: should perform significantly better than previous standard Competition: should be flexible enough to allow competition between manufactures based on technical merit. Only standardize bit-stream syntax and reference decoder Independence from transmission and storage media: should be flexible enough to be used for a range of applications. Forward compatibility: should decode bit-streams from prior standard 2

13 Backward compatibility: prior generation decoders should be able to partially decode new bit-streams H.264 Standard The most recent video compression standard, H.264 was finalized in May 2003 by the International Telecommunications Union (ITU) and the International Standards Organization(IS0)[1]. H.264, also known as MPEG-4 Part 10 and Advanced Video Coding, describes and defines a method of coding video that can give better performance than any of the preceding standards. Using H.264, it is possible to compress video into a smaller space, which means less transmission bandwidth and/or less storage space when required. H.264 has more options and parameters compared to any of the previous standards [1]. Tuning these parameters properly delivers high compression performance; tuning them improperly leads to poor-quality pictures and/or poor bandwidth efficiency. A standout feature of H.264 is its flexibility, coming with several tools for reducing redundant video information. This allows H.264 to vary from being highly complex to a rather simple algorithm, depending on the quality requirements. In addition to these tools, the H.264 standard defines 17 sets of capabilities, or profiles, that allow for this flexibility [1]. Each profile is targeted for a specific application ranging, ranging from high quality 3D stereoscopic video compression to a relatively low quality 2D video streaming. 1.3 H.264 Overview The H.264 encoding process consists of three steps to produce a compressed H.264 bitstream: prediction, transformation, and encoding. The H.264 decoding process performs the complementary process to produce a decoded video sequence. The decoded version is, in general, not an identical to the ordinal sequence because H.264 is a lossy compression format. 3

14 The structure of a typical encoder is shown below. Data is segmented in units of a macroblock (MB), which correspond to 16x16 group of displayed pixels. A prediction MB is generated and subtracted from the current MB to form a residual MB. The residual MB is transformed, quantized and encoded. Meanwhile, the quantized data is re-scaled,inverse transformed, and added to the prediction MB to form a reconstructed MB which is stored for later predictions. 1.4 Prediction H.264 supports a wide range of prediction options that include Intra prediction: Prediction formed from previously encoded data within the current frame. Inter prediction: Prediction formed using motion compensation from previously coded frames. Multiple prediction block sizes: Used in both intra and inter prediction in order to form more accurate predictions. Multi Frame Prediction: Used in inter prediction in order to form more accurate predictions. Skip Mode: no macroblock data or residual data is coded. Intra and inter prediction are discussed in more detail in the following sections. Macroblocks are grouped into slices which are processed in the order of a raster scan. A picture, a array of luma samples and two corresponding chroma samples, may be split into one or several slices as shown in 1.1. A slice be coded using different coding types which include: I Slice: A slice in which all MBs of the slice are coded using intra prediction. 4

15 Figure 1.1: Picture divided into three slices P Slice: In addition to the coding types of the I slice, some MB of the P slice can also be coded using inter prediction with at most one motion-compensated prediction signal per prediction block. B Slice: In addition to the coding types available in a P slice, some MBs of the B slice can also be coded using inter prediction with two motion-compensated prediction signals pre prediction block. The three slices mentioned above are very similar to to those in previous standards with the exception of the use of reference pictures as discussed later on. Two new coding types for slices are SP and SI slices. For more information, refer to [2] Intra Prediction A prediction that is formed based on spatial data is known as intra prediction. MBs formed using intra prediction are known as I MBs. Intra prediction uses samples from adjacent, previously coded blocks to predict values in the current MB. H.264 supports three choices of intra prediction block sizes for the luma component: 16x16, 8x8, and 4x4. Figure 1.2 shows the prediction samples for a 4x4 luma block. A single predication block is generated for each chroma component. Each 5

16 prediction block is generated using one of many possible prediction modes. Table 1.2 summarizes these modes. Figure 1.2: Prediction Samples for luma 4x4 prediction The choice of intra prediction block size for the luma component tends to be a trade-off between prediction efficiency and the number of bits required to code the prediction mode. Smaller blocks tend to give more accurate predictions but more bits are required to code the prediction choices. Larger blocks tend to give less accurate predictions but require fewer bits to code the prediction choice. H.264 supports a number of intra prediction modes for different block sizes. Block sizes of 16x16, 8x8, and chroma blocks each use a subset of the nine prediction modes for 4x4 luma blocks. Refer to [3] for a complete description of prediction modes for all block sizes Inter Prediction A prediction that is formed based on temporal data is known as inter prediction. This involves two processes; motion estimation and motion compensation. Motion estimation consists of locating a search region and forming a prediction MB. Motion compensation consists of subtracting the predicted block from the current MB to form the residual that is to be coded and transmitted. The 6

17 Table 1.2: Luma Prediction Modes, 4x4 prediction Mode 0 (Vertical) Mode 1 (Horizontal) Mode 2 (DC) Mode 3 (Diagonal Down-Left) Mode 4 (Diagonal Down-Right) Mode 5 (Vertical-Left) Mode 6 (Horizontal-Down) Mode 7 (Vertical-Right) Mode 8 (Horizontal-Up) The upper samples A,B,C,D are extrapolated vertically. The left sample I,J,K,L are extrapolated horizontally. All samples in P are predicted by the mean of samples A..D and I..L. The samples are interpolated at a 45 angle between lower-left and upper-right. The samples are extrapolated at a 45 angle down and to the right. Extrapolation at an angle of approximately 26.6 to the left of vertical. Extrapolation at an angle of approximately 26.6 below horizontal. Extrapolation at an angle of approximately 26.6 to the right of vertical. Interpolation at an angle of approximately 26.6 above horizontal. block of samples to be predicted can be predicted using a range of block sizes. The macroblock can be split into one, two, or four macroblock partitions: one 16x16 partition (the entire MB) two 8x16 partitions two 16x8 partitions four 8x8 partitions If an 8x8 partition is chosen, then each 8x8 block of samples may be further divided into a submacroblock consisting of one, two, or four sub-macroblock partitions: one 8x8 partition two 8x4 partitions 7

18 two 4x8 partitions four 4x4 partitions Figure 1.3 illustrates MB partitioning. Figure 1.3: Macroblock Partitioning for Inter prediction. Top: Segmentation of MBs, Bottom: segmentation of 8x8 partitions The prediction signal for each MB is obtained by displacing an area of the corresponding reference pictures, which is specified by a translational motion vector and a reference picture index. Each partition requires a reference picture index and motion vector. If an 8x8 partition is used, each sub-partition requires a motion vector as well. It is possible that 16 motion vectors are required for a single P MB. The motion vector components are differentially coded uses either median or directional prediction from neighboring blocks. H.264 has the capability of interpolating reference pictures. Each partition in an inter-coded MB is predicted from an area of the same size in a reference picture. The motion vector has 1 4 pixel resolution for the luma component and 1 8 pixel resolution for the chroma components. The sub-pixel positions do not exist in the reference picture so it is necessary to create them using interpolation 8

19 from nearby image samples. Interpolating the reference picture at the half and quarter pixel locations leads to more accurate motion representation. More detailed information on fractional sample accuracy is presented in [4]. H.264 supports multipicture motion-compensated prediction [5] [6]. This means that more than one prior coded picture can be used as reference for the motion-compensation process. Figure 1.4 illustrates this concept. Multipicture motion-compensated prediction requires both the encoder and decoder to store the reference pictures used for inter prediction in the decoded picture buffer (DPB). Unless the size of the DPB is set to one picture, the index at which the reference picture is located inside the DPB must be signalled. The reference index parameter is transmitted for each motioncompensated 16x16, 16x8, 8x16, or 8x8 luma block. Motion compensation for smaller regions than 8x8 use the same reference index for prediction of all blocks within the 8x8 region. Figure 1.4: Multiframe Motion Compensation. Motion vector and reference index are transmitted An additional MB mode for a P MB is called skip, or P Skip. For this coding type, neither a quantized prediction error signal, nor motion vector or reference index parameter is transmitted. P Skips are useful for temporally homogeneous regions; which can be represented with very few bits. The concept of inter prediction using B slices is generalized in H.264/AVC [7]. This extension refers back to [8] and is further investigated in [9]. Unlike previous standards, other pictures can reference pictures that contain B slices for motion-compensated prediction which is dependent on 9

20 the memory management control operation of the DPB. B slices utilize two distinct lists of reference pictures, list 0 and list 1. The reference pictures may include pictures before and after the current picture in display order. A prediction block for a B MB is generated from two prediction regions in reference pictures. Optionally, the prediction block may be weighted according to the temporal distance between the current and reference picture(s), known as weighted prediction. In B slices, four different types of inter-picture prediction are supported: list 0, list 1, bipredictive, and direct prediction. For list 0 and list 1 prediction, and prediction block is generated from either a picture in list 0 or list 1. The respected motion vector and reference picture index (if necessary) are coded and transmitted. Bi-prediction consists of forming a prediction block formed by a weighted average of motion-compensated list 0 and list 1 prediction signals. Direct prediction mode is inferred from previously coded syntax elements and can be either list 0 or list 1 prediction or bi-predictive. Direct mode is similar to the prediction mode P skip. The difference being that direct mode encodes and transmits an error signal for the MB. If no prediction error is encoded and transmitted for direct mode, this is known as B Skip mode; which is coded very similar to a P skip. 1.5 Transform, Scaling, and Quantization Similar to previous video coding standards, H.264 utilizes transform coding of the residual data. However, H.264 performs the transformation on 4x4 blocks and instead of a 4x4 discrete cosine transform (DCT), an integer transformation is used with similar properties as the 4x4 DCT. To ease the memory requirement of H.264, the integer transform was developed such that there would be a zero mismatch between the forward and inverse transforms [1]. Also, because it is an integer transform, there is no loss of decoding accuracy due to rounding. The DCT operates on X, a block of NxN samples, typically image samples or residual values after prediction to create Y, an NxN block of coefficients. 10

21 Equation 1.1 shows the DCT integer transformation a a a a Y = AXA T = b c c b a a a a [X] a b b a Where a = 1 2, b = 1 2 cos ( ) π 8, c = 1 2 cos ( ) 3π 8 a b a c a c a b a c a b a b a c (1.1) The DCT shown in Equation 1.1 can be factorized to form the H.264 integer transform shown in Equation 1.2. Y = CXC T E = [X] where a = 1 2, b = 1 2 cos ( ) π 8, c = 1 2 cos ( ) 3π a 2 ab 2 a 2 ab 2 ab 2 a 2 ab 2 b 2 ab b 2 ab a 2 ab 2 b 2 ab b (1.2) The multiplication performed at the end of the integer transform is absorbed into the quantization process. Thus, the core portion of the integer transform can be performed using addition, subtraction, and shifts. This is the same for the inverse transformation show in Equation 1.3. Further discussion on the specifics of the H.264 integer transform can be found in [10]. Y = C T i (Y E i)c i = where a = 1 2, b = 1 2 cos ( ) π 8, c = 1 2 cos ( ) 3π 8. [X] a 2 ab a 2 ab ab b 2 ab b 2 a 2 ab a 2 ab ab b 2 ab b (1.3) Hadamard Transform If the macroblock is predicted using 16x16 intra prediction or if the data represents chrominance, the Hadamard Transform is performed on the lowest or DC coefficients [3]. The DC coefficients 11

22 are extracted and stored as a separate 4x4 block of data if working with a 16x16 luma macroblock as shown in Figure 1.5. In the case of chroma data, a 2x2 Hadamard transform is performed on the 2x2 block of chroma DC coefficients. Figure 1.5: Extracting DC Coefficients The 4x4 block of DC coefficients (X DC ) are then transformed to obtain (Y DC ) using Equation 1.4. If working with a 2x2 block of data, the coefficients are transformed using Equation 1.5. The Hadamard transform provides additional data reduction in cases where prediction methods create an abundance of DC data. Further information on the motivation for the Hadamard transform can be found in [7] Y DC = [X DC] (1.4) Y DC = [ ] [ ] [X 1 1 DC ] 1 1 (1.5) 12

23 1.5.2 Quantization A quantizer maps a signal with a range of values X to a quantizer signal with a reduced range of values Y. It should be possible to represent the quantized signal with fewer bits than the original since the range of possible of possible values is smaller. H.264 uses a scalar quantizer that maps one input signal to one quantized output value. A simple scalar quantization process consists of round a fractional number to the nearest integer. This process is lossy since it is not possible to determine the exact value of the original signal. A quantization parameter is used for determining the quantization of transform coefficients in H.264. The parameter can take 52 values. The values are arranged so that an increase of 1 in quantization parameter means an increase of quantization step size by approximately 12% [7]. Typically, the result is a block in which most or all of the coefficients are zero, with few non-zero coefficients. Setting a QP to a high value means that more coefficients are set to zero, resulting in high compression at the expense of poor decoded image quality. Setting QP to a low value means that more non-zero coefficients remain after quantization, resulting in better image quality at the decoder but also in lower compression. The quantization process performs both the scaling required by the integer transform and the actual data quantization. H.264 uses a scalar quantizer, which is also integer based [11]. The basic forward quantization process is shown in 1.6. ( ) Y Z = round Q step (1.6) 13

24 1.6 Entropy Coding The entropy coding portion of the H.264 is where all the necessary data to recreate the video file is converted to binary. An H.264 file is organized into syntax layers as shown in figure 1.6. The H.264/AVC standard supports to methods of entropy coding. Figure 1.6: H.264 Syntax Layers Exp-Golomb Coding The simpler method uses a single codeword table for all syntax elements except the quantized transform coefficients. This method is called exp-golomb coding and consists of a very simple and regular decoding properties. This coding method has the advantage of avoiding creating a variable length coded table for each syntax element. Instead, only the mapping to the single codeword table is customized according to the data statistics. 14

25 1.6.2 CAVLC For transmitting the quantized coefficients, a more efficient method called Context-Adaptive Variable Length Codding (CAVLC) is employed. CAVLC uses VLC tables for various syntax elements are switched depending on already transmitted syntax elements. Since the VLC tables are designed to match the corresponding conditional statistics, the entropy coding performance is improved in comparison to a single VLC table [7]. CAVLC is required for all profiles of the H.264 standard. Further details on the overview of CAVLC can be found in [7] CABAC The efficiency of entropy encoding can be improved further with Context-Adaptive Binary Arithmetic Coding (CABAC)[12]. CABAC uses statistics of already coded syntax elements are used to estimated conditional probabilities. These conditional probabilities are used for switching several estimated probability models. Compare to CAVLC, CABAC typically provides a reduction in bit rate between 5%-15% [7]. More detailed information about CABAC can be found in [12]. 1.7 Profiles and Levels The H.264 standard specifies profiles, each contains a subset of the coding tools available in the H.264 standard. A profile defines a set of coding tools or algorithms that can be used in generating a conforming bitstream [1]. A level places constraints on certain key parameters of the bitstream such as the maximum number of frames per second for a given resolution. All decoders that conform to a specific profile must support all the features of that particular profile. Encoders are not required to make use of any particular set of features supported in a profile but have to provide conforming bitstreams. H.264 defines three profiles; baseline, main, and extended. Figure 1.7 illustrates these profiles and their respected features. A subset of baseline, constrained baseline, is also defined. 15

26 The baseline profile is intended for low delay applications such as mobile transmission [1]. The extended profile is a superset of the baseline profile, adding further tools that my be beneficial for efficient network streaming of H.264 data. The main profile is a superset of constrained baseline profile and adds tools that may be suitable for broadcast and entertainment applications. Figure 1.7: H.264 Profiles 1.8 Mode Selection Many coding methods have been presented in the previous sections. Figure 1.8 illustrates all the prediction possibilities for a macroblock. These include: Skip Mode: no information sent for MB 16

27 Four intra-16x16 modes Nine intra-4x4 modes, with a different choice possible for each 4x4 block 16x16 inter mode: prediction from reference picture(s) from one P or B MB or two B MB lists. 8x16 inter mode: prediction from multiple reference pictures as above, with the option of different reference picture(s) for each partition. 16x8 inter mode: same prediction choices as above. 8x8 inter mode: reference picture choices as above, with further sub-division of each 8x8 partition into 8x4, 4x8, or 4x4 sub MB partitions. In addition to the prediction mode, the encoder can choose to change the QP as well as within each inter mode the encoder has a wide choice of possible motion vectors (discussed in chapter 2). There are an enormous amount of options for coding each MB. Each combination of coding parameters will tend to generate a different number of coded bits which can range from very low (skips) to high (intra) and a different distortion. The ultimate goal of a video encoder aims to minimize coded bitrate and maximize decoded quality. This is a very difficult goal due to the large number of coding options as well as deciding the best tradeoff between minimizing bitrate and minimizing distortion. The three measurements that are taken into account when coding a MB are: Header bits: The number of bits required to signal the MB mode, plus any prediction parameters such as intro mode, reference choices and/or motion vector difference. Coefficient bits: The number of bits required to code the quantized transform coefficients. 17

28 Figure 1.8: Available Prediction Modes SSD: (Sum of Square Differences) Distortion of the decoded, reconstructed MB, measured in sum of squared distortion (equation 1.7) where x, y are the sample positions in a block, b(x, y) are the original sample values and b (x, y) are the decoded sample values at each sample position. SSD = x,y ( b (x, y) b (x, y)) 2 (1.7) 18

29 1.8.1 Rate Distortion Optimized Mode Selection Rate Distortion Optimization (RDO) mode selection is a technique used for choosing the coding mode of a MB based on the rate and distortion cost [1]. The bitrate cost R and distortion cost D are combined in a single cost function J shown in Equation 1.8. The RDO mode selection algorithm attempts to fine a mode that minimizes the joint cost J. The trade-off between rate and distortion is controlled by the Lagrange multiplier λ. J = D + λr (1.8) 1.9 Motivation and Organization Because of the many encoding options, this thesis presents a rate distortion optimization technique in order to incorporate multiple block sizes, multi reference frames, and B frames. This thesis is divided into four additional chapters. Chapter 2 presents interprediction in terms of multi-frame coding. Chapter 3 presents B frame coding in more detail. Chapter 4 will discuss RDO implemented on multi-frame coding and B frames and compares the compression performance to a straight up error decision process. Finally, chapter 5 provides details on future work and conclusions concerning the implementations and performance of the proposed RDO scheme. 19

30 CHAPTER II Multi Frame Prediction 2.1 Interprediction Overview A prediction formed temporally is referred to as interprediction. Inteprediction requires the use of at least one picture that has previously been encoded, a reference picture. The basic steps to interprediction are listed below. Before adding B frames to the encoder, given the current state of the encoder, a logical stepping block is to add the capabilities of multi frame prediction since B frames require more than a single reference frame in order to be useful. The following sections discuss the process of adding multi frame prediction capabilities. Interpolate the picture(s) in the DPB to generate 1 4 same positions in the luma component and 1 8 sample positions in the chroma component. Choose an inter prediction mode. This involves the choice of reference picture, choice of macroblock partition and sub-partition, and the choice of prediction types which include list 0 and list 1 depending on the MB type. Choose motion vectors Predict the motion vectors from previously-transmitted vectors and generate motion vector differences. 20

31 Code the MB type, choice of prediction references, motion vector differences, and residual data. Apply a deblocking filter. Each partition in an inter-coded MB is predicted from an area of the same size in a reference picture. The offset between the two areas, the motion vector, has 1 4 pixel resolution for the luma components and 1 8 pixel resolution for the chroma components. Sub-pixel motion estimation is possible in H.264. Refer to [1] for more information. 2.2 Syntax Overview Figure 1.6 shows an overview of the H.264 syntax elements. It is be worthwhile to discuss some of these syntax for the future discussion. Coded H.264 data is stored or transmitted in a series of packets call Network Abstraction Layer (NAL) units. The first NAL unit to be discussed is the Sequence Parameter Sets (SPS). This particular NAL units carries coding parameters common to an entire video sequence. These parameters include the profile, constraints on the profile, number of reference frames, and the size of the image. Picture Parameter Sets (PPS) contain common parameters to a sequence of coded frames such as entropy encoding type, number of active reference pictures, and initial QP. A complete list of SPS and PPS parameters can be found in [3]. Another NAL unit of interest is the slice layer. The slice layer is made up of the slice header which conveys information common to all macroblocks in the slice, such as slice type which determines which macro blocks types are allowed. For example, I MBs are permitted in P and B slices. The slice layer also provides the frame number in which the slice corresponds to, the reference picture settings, and the default QP. A full list of the syntax elements found in the slice layer can be found in [3]. 21

32 The slice data sections contains a series of MBs that make up that particular slice. The proposed implementation contains one slice per frame and all MBs within that slice are equivalent to the slice type. This means that if a slice type is set as P type, then only P MBs are contained within that slice. Each MB in the slice contains what is known as the Macroblock Layer. An overview of the MB layer for the Baseline profile is shown in 2.1. If the mb pred or sub mb pred process yields a coded block pattern of zero, indicating that the transform and quantize process returned zero coefficients, the rest of the encoding processes process can be skipped. Each MB contains a mb pred process or a sub mb pred process if sub-partitions are present. An simple overview of each of these processes are shown in figure 2.2 and figure 2.3. As will be shown later, the reference indices and motion vectors differences may not be present under certain conditions thus it will not be necessary to encode. Figure 2.1 also indicates the residual process. This process involves implementing CAVLC or CABAC on the transformed and quantized coefficients. The CAVLC process does not change for multi frame prediction and so will not be discussed any further. CABAC on the other hand does change due to the fact that encoding MB data is done in the CABAC process as opposed to look up tables as done by CAVLC. CABAC has not been modified in the proposed encoder to support multi frame prediction. 2.3 Picture Ordering Before discussing the topic of multi frame encoding, it is important to distinguish three different orderings of pictures: Decoding order - the order in which pictures are decoded from the bitstream. Display order - the order in which pictures are output for display. Reference order - the order in which pictures are arranged for inter prediction of other pictures. 22

33 Figure 2.1: Macroblock Layer Overview: Baseline The parameter frame num, decoded from the slice header, determines the decoding order of pictures. In most cases, frame num for each decoded picture increases by one compared with the previous reference frame in decoding order. Display order is determined by the parameters Top- FieldOrderCount and BottomFieldOrderCount, collectively known as Picture Order Count (POC). The display order is derived from the the sliced header using three methods: Type 0: The least significant bits of POC are sent in every slice header. Allows maximum flexibility but require the most bits compared to other methods. Type 1: A cycle of POC increments is set up in the sequence parameter set and POC changes according to this cycle unless otherwise signalled in the slice header using a Delta offset. The 23

34 Figure 2.2: mb pred syntax overview cycle defines the interval between frames used for reference, plus a POC offset to frames no used for reference. Only the Delta offset value is encoded and transmitted. Type 2: POC is derived directly from frame num and display order is the same as decoding order. The proposed encoder uses Type 0 for display order. An example using only P frames is shown in figure2.4. Starting with the I slice, frame num starts at a value of zero. If the previous picture is used for reference, frame num will increment by a value of one. Since all frames in this example are used for reference, frame num is incremented by one for each frame. POC is incremented by two for every complete frame, i.e. every two fields. Display order is then determined by the values of POC. In this particular sequence, decoding order and display order are the same. 24

35 Figure 2.3: sub mb pred syntax overview 2.4 Reference Picture Lists A picture that is coded and available for reference is stored in the DPB and marked as one of the following: short term reference picture, indexed according to frame num (PSlice) or POC (BSlice) long term reference picture The proposed encoder focuses on short term reference pictures. More information on long term reference pictures can be found in [3]. Reference pictures are ordered in one or two lists prior to encoding or decoding a frame. In the case of P slices, a single list, list0 is used. The default 25

36 Figure 2.4: Display Order Example, Type 0 order of list0 depends or decoding order. The lists orders are important, since indices to reference pictures earlier in the list require few bits to signal. Hence the default orders are organized so that the reference pictures temporally closer to the current picture occur early in the list since these are most likely to be the best prediction match for the current picture. Figure 2.5 shows an example of list0 ordering for P slices. The default reference picture list order can be changed in order to place a particularly useful reference frame earlier in the list than its usual position. This feature is not implemented in the proposed encoder. 2.5 Exp-Golomb Coding Exponential Golomb coding is utilized for most of the syntax elements outside of residual data. An Exp-Golomb codeword consists of a prefix of 0s followed by a stop bit 1 and a suffix containing a binary number related to the value being encoded, codenum. The length of the suffix is 26

37 Figure 2.5: Reference Picture Order Example: P Slices identical to the number of zeros found in the prefix. The codenum derived from the suffix is interpreted differently based on the type of Exp-Golomb code used. By assigning short codewords to frequently-occurring data symbols and long codewords to less common data symbols, the data may be represented in a compressed form. Table 2.1 illustrates the first few Exp-Golomb codes. Table 2.1: Exp-Golomb Codewords code num CodeWord The variable codenum can either directly represent the syntax element value to be coded or used in a mapping process define in [3]. Multiple mapping methods are necessary since Exp-Golomb by 27

38 itself cannot support signed values. An additional reason is that a syntax element may belong to a set of elements and the number of elements in that set is less than the value of the syntax element itself. Exp-Golomb then maps that element to an index in the set, reducing the length of the codeword. Table 2.2 gives an overview of the mapping processes. The mapping process te is called upon very little through the coding process. One of the few exceptions is the reference index syntax element. Caution must be used when encoding this particular syntax element since there are multiple factors that determine if the reference index is part of the bitstream or not, as will be discussed more in a later section. Table 2.2: Mappings to codenum Mapping type ue te se me Description Unsigned direct mapping: Used for macroblock type and others. Truncated mapping: if the largest value of the syntax element is 1, then a single bit is sent, otherwise ue mapping is used. Signed mapping: used for motion vector difference, delta QP, and others. Mapped symbols: syntax element is mapped according to a table specified in [3]. 2.6 Motion Vector Prediction In order to save on the number of bits coded, a predicted motion vector is determined in the inter prediction process. The predicted motion vector is then subtracted from the actual motion vector to form the motion vector difference; syntax element mvd lx or sub mvd lx if sub partitions are present and X = 0 or 1 indicating the proper list. Encoding a motion vector can cost a significant number of bits, especially if small partition sizes are chosen. Motion vectors for neighboring partitions are generally highly correlated and so each motion vector is predicted from the surrounding, 28

39 previously encoded partitions. These partitions may lie within the current MB or a neighboring MB. The method of forming the predicted motion vector, MV P, depends on the motion compensation partition size and on the availability of nearby vectors. Figure 2.6 shows neighboring blocks A,B, and C for 16x16 MBs only. Figure 2.7 shows neighboring blocks A,B, and C for a 16x16 MB with different partition sizes as the neighboring blocks. The MV P is the median of the motion vectors for partitions A,B, and C. Figure 2.6: Current and neighboring partitions: 16x16 partitions If one or more of the previously transmitted blocks shown in 2.6 or 2.7 is unavailable, the choice of MV P is modified accordingly. Full details of these modifications can be found in [3]. A partition may not be available due to the partition being outside the current picture, outside the current slice, or the partition was coded as a skipped MB. 2.7 Multi Frame Encoding A simple block match algorithm for motion estimation can be described as: creating a window that consisted of N search points 29

40 Figure 2.7: Current and neighboring partitions: different partitions sizes calculate the SSE for each search point the block with the least SSE is the best candidate determine the corresponding motion vector for the best candidate For the addition of multi frame coding, several changes must be made to the encoding process. The first of these changes is in the picture parameters sets (SPS). This is the location where the maximum number of reference frames is determined by parameter num ref frames. The second change is in the picture parameters sets (PPS). The PPS contains a parameter called num ref idx l0 minus1. This parameters tells the decoder the number reference pictures that are contained in list0. This does not necessarily mean the maximum number of reference frames as will be shown in B frames. For this discussion, the maximum number of reference frames will also be the number of frames contained in list0. For example, if the number of reference frames is chosen as 3, the value of 30

41 num ref idx l0 minus1 can include 0,1,or 2 but cannot exceed the maximum number of reference frames minus one. The third syntax element that must be set with caution falls within the slice header. The slice header contains the parameter num ref idx active override flag. The decoder determines the number of active reference frames from num ref idx l0 minus1 in the PPS. However, the number of active reference frames is not always at this value. If this syntax element is set, it means that the DPB is not full and the number of reference pictures must be overridden by the associated syntax element num ref idx l0 active override flag. For instance, if the current num ref frames = 3, frames two and three will only have one and two reference frames available for coding respectively. These number of reference frames must be recognized by the decoder. Therefore in the slice header of each of these frames, num ref idx active override flag will be set to one and num ref idx l0 minus1 will be set to zero and one respectively. When the picture buffer becomes full, num ref idx active override flag is set to zero and the number of active reference frames is inferred from the SPS in order to save bits. The final parameter that must be adjusted from single frame coding exists in the macroblock/submacroblock layer. A reference index, syntax element ref idx l0 must be coded and transmitted indicating which reference frame in list0 is being used for inter prediction. In the case of single reference frame prediction, this ref idx l0 is inferred to zero by the decoder. Multi frame prediction requires that ref idx l0 be coded and transmitted. Of course if only one reference frame is active, indicated by num ref idx l0 minus1 in the slice header, it is not necessary to encoded and transmit ref idx l0. After applying the discussed changes to the syntax elements, the following tests are generated using the proposed encoder on foreman, flower, and flyby video files [13]. The tests consist of coding up to five reference frames for 16x16 MBs only. QPs range from 10(upper right) up to 31

42 40(lower left). The PSNR for the luma component wisas calculated for the entire sequence. As expected, in each case there is a slight improvement in bitrate for all QP values. 55 Foreman Multi Frame Coding: Performance 16x16, 100 frames at 25 FPS PSNR (Y) Ref 2 Ref 3 Ref 4 Ref 5 Ref Rate (kbps) Figure 2.8: Multi Frame Prediction: Foreman The encoding time for each sequence in seconds is shown in Figures 2.11 though 2.13: With the exception of Foreman,the noticeable difference for all three tests is the transition from a single reference frame to two reference frames. This appears to be the most beneficial for slow moving image such as flower and flyby. Foreman has relatively high motion, particularly around the face and mouth regions. The results show more of an increase in performance when transitioning 32

43 55 Flower Multi Frame Coding: Performance 16x16, 100 frames at 25 FPS PSNR (Y) Ref 2 Ref 3 Ref 4 Ref 5 Ref Rate (kbps) Figure 2.9: Multi Frame Prediction: Flower from two reference frames to three reference frames. Flower also follows this trend to a degree due to the motion in that particular sequence. 2.8 Conclusions In this chapter, a detailed description of what syntax elements from the proposed encoder needed to be modified in order to support multiple reference frames. This functionality is imperative for the implementation of B frames later on. In addition, reference list management was also introduced for P slices. Chapter 3 will expand on this idea to incorporate B slices. A rate distortion curve was generated for three videos containing different resolutions. The results showed an increase in 33

44 52 FlyBy Multi Frame Coding: Performance 16x16, 100 frames at 25 FPS PSNR (Y) Ref 2 Ref 3 Ref Rate (kbps) Figure 2.10: Multi Frame Prediction: Flyby performance for each additional reference frame. The negative affects off multi frame coding are in the complexity of the encoder. More memory must be allocated for reference frame storage as well as additional processing time for the block search algorithm. In applications when speed is a high priority, multi frame encoding must be exercised with caution. However, if quality is the goal of the decoder, multi frame prediction certainly would be useful. 34

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