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HEVC CABAC

Group Project Report

DR.K.R.RAO

COURSE:EE5359–Topics in Signal Processing

SPRING2016

Submitted by

Mohammed Mahmood Quraishi(1001151028) Satya avasarala(1001090898) Sai Kumar Pola(1001110666)

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Table of Contents 1. Objective................................................................................................................................ ……..5 2. Motivation- Video Compression and Its Need......................................................................................5 3. Evolution of Video Coding Standards..............................................................................................6 3.1. AVC/H.264.................................................................................................................................6 3.1.1 AVC/H.264 Encoder..................................................................................................................7 3.2 Features.........................................................................................................................................8 3.3 Applications....................................................................................................................................9 3.4. Disadvantages of AVC/H.264...........................................................................................................9 4. HEVC ................................................................................................................................................10 4.1. Versions.......................................................................................................................................10 4.1.1 Version 1 ....................................................................................................................................10 4.1.2Version 2.....................................................................................................................................10 4.1.3Version 3......................................................................................................................................10 4.2.1 HEVC Encoder and Decoder........................................................................................................11 4.2.2 Decoder and Steps ......................................................................................................................11 4.3 Features..........................................................................................................................................12 . 4.3.1 Image Partitioning.......................................................................................................................12 4.3.2 A Picture Representing CT, CU, PU............................................................................................12 4.3.3 Coding Efficiency........................................................................................................................13 4.3.4 Coding Tools................................................................................................................................14 4.3.4.1 Coding Tree...............................................................................................................................14 4.3.4.2 Parallel Handling Tools...............................................................................................................14

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4.3.4.3 Wave front Parallel Processing WPP..........................................................................................14 4.3.5 Other Coding Tools .......................................................................................................................15 4.3.5.1. Entropy Coding.........................................................................................................................15 4.3.5.2. Intra Prediction.........................................................................................................................15 4.3.6. Motion Vector Prediction ............................................................................................................16 4.3.7. Inverse Transform..........................................................................................................................17 4.3.8 De-blocking Filter............................................................................................................................17 4.3.9. Sample Adaptive Effect .................................................................................................................17 4.4. CABAC and Its Overview .....................................................................................................................18 4.4.1. CABAC Algorithm ...........................................................................................................................18 4.5. HEVC CABAC and Its Main Steps.........................................................................................................18 4.5.1. Binarization.....................................................................................................................................18 4.5.2. Arithmetic Coding...........................................................................................................................19 4.5.3 Context Selection.............................................................................................................................19 4.6. CABAC Encoder....................................................................................................................................20 4.7. The Arithmetic Decoding Procedure ..................................................................................................20 4.8. Throughput Improvement CABAC.......................................................................................................20 4.8.1. Reduce Total number of bins.........................................................................................................21 4.8.2. Reduce Total number of Context Coded bins..................................................................................21 4.8.3. Grouping of By-pass Bins...............................................................................................................22 4.9. Conclusion..........................................................................................................................................24 4.10. References........................................................................................................................................26

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ACRONYMS

AVCHD: Advance Video Coding High Definition ATSC: Advance Television System Committee CABAC: Context Adaptive Binary Arithmetic Coding CAVLC: Context Adaptive Variable Length Coding CCTV: Closed Circuit Television CPU: Central Processing Unit CTB : Coding Tree Block DCT : Discrete Cosine Transform DVB: Digital Video Broadcasting FSM : Finite State Machine HDTV: High Definition Television HEVC: High Efficiency Video Coding IDR: Instantaneous Video Refresh ISDBT: Sistema Brasileiro de Televisão Digital ISO: International Organization for Standardization

IEC: International Electro-Technical Commission JCT-VC: Joint Collaboration Team On Video Coding AVC : Advance Video Coding CTU : Coding Tree Unit CU : Coding Unit PU : Prediction Unit MPEG : Moving Picture Experts Group HDTV : High Definition Television PSNR : Peak Signal To Noise Ratio ITU-T: International Telecommunication Union- Telecommunication Standardization Sector. JCT: Joint Collaborative Team. JCT-VC: Joint Collaborative Team on Video Coding. JM: H.264 Test Model. JPEG: Joint Photographic Experts Group. MC: Motion Compensation. ME: Motion Estimation. MPEG: Moving Picture Experts Group. MSE: Mean Square Error. PB: Prediction Block. QP: Quantization Parameter SAO: Sample Adaptive Offset. VCEG: Video Coding Experts Group. SSIM: Structural Similarity Index. TB: Transform Block.

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TU: Transform Unit. VCEG: Visual Coding Experts Group. 1.OBJECTIVE:

The goal of this project is to give an insight of the CABAC(Context Adaptive Binary Arithmetic

Coding) entropy coding method that was as of late developed with HEVC standard (ITU - T

Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG)

institutionalization associations) in the year 2013. HEVC (H.265) standard is the most recent

upgraded video coding standard which wanted to enhance the rendered details of its previous

standard MPEG-4 (H.264).The primary objective of the HEVC standardization is to enable

significantly improved compression performance relative to existing standard AVC. For

comparative video quality, HEVC bit-streams produce much better video quality than that of

H.264. HEVC uses variable block length coding to perform encoding operation. Hence, it uses

different sizes of integer transforms HEVC is gives support to resolutions up to Ultra High

Definition (UHD),4K video coding.

2.VIDEO COMPRESSION AND ITS MOTIVATION:

We need to compress video in practice since:

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Uncompressed video data are huge. In HDTV, the bit rate easily exceeds 1 Gbps. -- big problems

for storage and network communications[3]. For example: One of the formats defined for HDTV

broadcasting within the United States is 1920 pixels horizontally by 1080 lines vertically, at 30

frames per second. If these numbers are all multiplied together, along with 8 bits for each of the

three primary colors, the total data rate required would be approximately 1.5 Gb/sec. Because of

the 6 MHz. channel bandwidth allocated, each channel will only support a data rate of 19.2

Mb/sec, which is further reduced to 18 Mb/sec by the fact that the channel must also support

audio, transport, and ancillary data information. As can be seen, this restriction in data rate

means that the original signal must be compressed by a figure of approximately 83:1[2]. This

number seems all the more impressive when it is realized that the intent is to deliver very high

quality video to the end user, with as few visible artifacts as possible.

Lossy methods have to be employed since the compression ratio of lossless methods (e.g.,

Huffman, Arithmetic, LZW) is not high enough for image and video compression

The following compression types are commonly used in Video compression:.

Spatial Redundancy Removal – Intra-frame coding (JPEG)

Spatial and Temporal Redundancy Removal – Intra-frame and Inter-frame coding (H.261,

MPEG).

Block motion estimation.

Entropy Coding.

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3.EVOLUTION OF DIFFERENT VIDEO CODING STANDARDS:

Figure # 1 Evolution of video coding standards [1]

3.1AVC/H.264

H.264 also known as Advanced Video Coding (MPEG-4 AVC) is a video coding format is

developed by ITU-T ITU-T Video Coding Experts Group (VCEG) together with the ISO/IEC

JTC1 Moving Picture Experts Group (MPEG)[4].The H.264 standard can be viewed as a "

group of standards" composed of the profiles . The standard was developed jointly in a

partnership of VCEG and MPEG, after earlier development work in the ITU-T as a VCEG

project called H.26L. It is thus common to refer to the standard with names such as H.264/AVC,

AVC/H.264, H.264/MPEG-4 AVC, or MPEG-4/H.264 AVC. It is also referred to as "the JVT

codec", in reference to the Joint Video Team (JVT) organization that developed it[2]. For

example, the video compression standard known as MPEG-2 also as it was proposed by the

partnership between MPEG and the ITU-T, where MPEG-2 video is known to the ITU-T

community as H.262.

H.264 technology aims to provide good video quality at considerably low bit rates, at reasonable

level of complexity while providing flexibility to wide range of applications.[1] The MPEG-2

video coding standard (also known as ITU-T H.262) [2], which was developed about ten years

ago primarily as an extension of prior MPEG-1 video capability with support of interlaced video

coding, was an enabling technology for digital television systems worldwide. It is widely used

for the transmission of standard definition (SD) and high definition (HD) TV signals over

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satellite, cable, and terrestrial emission and the storage of high-quality SD video signals onto

DVDs.

H.264 is perhaps best known as being one of the video encoding standards for Blu-ray Discs; all

Blu-ray Disc players must be able to decode H.264. It is also widely used by streaming internet

sources, such as videos from Vimeo, YouTube, and the iTunes Store, web software such as the

Adobe Flash Player and Microsoft Silverlight, and also various HDTV broadcasts over terrestrial

(Advanced Television Systems Committee standards, ISDB-T, DVB-T or DVB-T2), cable

(DVB-C), and satellite (DVB-S and DVB-S2).

3.1.1 AVC /H.264 ENCODER [6]:

Figure # 2 AVC/H.264 ENCODER [2]

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3.2 Features

H.264/AVC/MPEG-4 contains various new components that permit it to pack video considerably

more productively than more seasoned principles and to give more adaptability to application to

a wide assortment of system situations. Specifically, some such key elements include:

Multi-picture between picture expectation including the accompanying elements:

Using previously encoded pictures as references in a optimum way than in previous standards,

allowing up to 16 reference frames (or 32 reference fields, in the case of interlaced encoding) can

be used. In profiles that support non-IDR frames, most levels specify that sufficient buffering

should be available to allow for at least 4 or 5 reference frames at maximum resolution. This is in

contrary to prior standards, where the limit was typically one; or, in the case of conventional "B

pictures" (B-frames), two. This particular feature usually allows slight improvements in bit rate

and quality in most scenes. But in certain types of sequences, such as those with repetitive

motion or back-and-forth sequence cuts or uncovered background areas, it allows a significant

reduction in bit rate while maintaining clarity.

Variable block-size motion compensation (VBSMC) with block sizes as large as 16×16 and as

small as 4×4, enabling exact division of moving regions[6]. The supported luma prediction block

sizes include 16×16, 16×8, 8×16, 8×8, 8×4, 4×8, and 4×4, many of which can be used together in

a single macroblock. Chroma prediction block sizes are correspondingly smaller according to the

chroma sub-sampling in use.

The ability to use multiple motion vectors per macro-block (one or two per partition) with a

maximum of 32 in the case of a B macro-block constructed of 16 4×4 partitions. The motion

vectors for each 8×8 or larger partition region can point to different reference pictures. Six-tap

filtering for derivation of half-pel luma sample predictions, for sharper sub-pixel motion-

compensation. Quarter-pixel motion is calculated by linear interpolation of the half-pel values, to

lessen processing power.[6]

Spatial prediction from the edges of neighboring blocks for "intra" coding, rather than the "DC"-

only prediction found in MPEG-2 Part 2 and the transform coefficient prediction found in H.263

version 2 and MPEG-4 Part 22a[3]. This includes luma prediction block sizes of 16×16, 8×8, and

4×4 (of which only one type can be used within each macro-block).

An in-loop de-blocking filter that helps prevent the blocking artifacts common to other DCT-

based image compression techniques, resulting in better visual appearance and compression

efficiency.

Coming to entropy coding it used both CABAC and CAVLC.CAVLC is some times referred as

Exp-golomb.

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3.3 Applications

The H.264 video format has a very broad application range that covers all forms of digital

compressed video from low bit-rate Internet streaming applications to HDTV broadcast and

Digital Cinema applications with nearly lossless coding. With the use of H.264, bit rate savings

of 50% or more compared to MPEG-2 Part 2 are reported. For example, H.264 has been reported

to give the same Digital Satellite TV quality as current MPEG-2 implementations with less than

half the bitrate, with current MPEG-2 implementations working at around 3.5 Mbit/s and H.264

at only 1.5 Mbit/s[5].AVCHD is a high-definition recording format designed by Sony and

Panasonic that uses H.264.AVC-Intra is an intra-frame a compression format, developed by

Panasonic.

To guarantee similarity and issue free reception of H.264/AVC, numerous benchmarks bodies

have altered or added to their video-related principles so that clients of these norms can utilize

H.264/AVC. Both the Blu-ray Disk design and the now-ceased HD DVD position incorporate

the H.264/AVC High Profile as one of 3 video compression formats[4]. The Digital Video

Broadcast venture (DVB) affirmed the utilization of H.264/AVC for telecast TV in late 2004.

The Advanced Television Systems Committee (ATSC) in the United States approved the use of

H.264/AVC for broadcast television in July 2008. It has also been approved for use with the

more recent ATSC-M/H (Mobile/Handheld) standard, using the AVC and SVC portions of

H.264.

XAVC is a recording group composed by Sony that uses level 5.2 of H.264/MPEG-4 AVC,

which is the largest amount bolstered by that video standard. XAVC can bolster 4K resolution

(4096 × 2160 and 3840 × 2160) at up to 60 frames for each second (fps). Sony has declared that

cameras that bolster XAVC incorporate two Cine Alta cameras—the Sony PMW-F55 and Sony

PMW-F5. The Sony PMW-F55 can record XAVC with 4K resolution at 30 fps at 300 M bit/s

and 2K resolution at 30 fps at 100 Mbit/s. XAVC can record 4K resolution at 60 fps with 4:2:2

chroma sub sampling at 600 Mbit/s.

The CCTV (Closed Circuit TV) and Video Surveillance markets have incorporated the

innovation in numerous items.

3.4 DISADVANTAGES OF AVC/H.264:

1.At the same bit rate HEVC performs far more better video quality compared to H.264[6].

2.H.264 encoding and decoding is more computationally complex than some other codecs such

as MPEG-4.

3. At the same bit rate HEVC performs far more better video quality compared to H.264.

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4 HEVC

HEVC was developed by the JCT-VC organization, a collaboration between the ISO/IEC MPEG

and ITU-T VCEG. The ISO/IEC group refers to it as MPEG-H Part 2 and the ITU-T as

H.265[1].

In most ways, HEVC is an extension of the concepts in H.264/MPEG-4 AVC. Both work by

comparing different parts of a frame of video to find areas that are redundant, both within a

single frame as well as subsequent frames[3]. These redundant areas are then replaced with a

short description instead of the original pixels. The primary changes for HEVC include the

expansion of the pattern comparison and difference-coding areas from 16×16 pixel to sizes up to

64×64, improved variable-block-size segmentation, improved "intra" prediction within the same

picture, improved motion vector prediction and motion region merging, improved motion

compensation filtering, and an additional filtering step called sample-adaptive offset filtering.

Effective use of these improvements requires much more signal processing capability for

compressing the video, but has less impact on the amount of computation needed for

decompression.

HEVC is protected by patents owned by various parties. Commercial use of HEVC technologies

requires the payment of royalties to licensors of HEVC patents, such as MPEG LA, HEVC

Advance, and Technicolor SA. The first version of HEVC was completed in January 2013[9].

The second version was completed and approved in 2014 and published in early 2015.

Additional 3D-HEVC extensions for 3D video were completed in early 2015. Further extensions

remain in development for completion in early 2016.

4.1 Versions[3]:

4.1.1 Version 1:On February 29, 2012, at the 2012 Mobile World Congress, Qualcomm

demonstrated a HEVC decoder running on an Android tablet, with a Qualcomm Snapdragon S4

dual-core processor running at 1.5 GHz, showing H.264/MPEG-4 AVC and HEVC versions of

the same video content playing side by side. In this demonstration, HEVC reportedly showed

almost a 50% bit rate reduction compared to H.264/MPEG-4 AVC. On April 13, 2013 first

approved version of the HEVC/H.265 standard containing Main, Main 10, and Main Still Picture

profiles.

4..1.2 Version 2:On April 3, 2013, ATEME announced the availability of the first open source

implementation of a HEVC software player based on the open HEVC decoder and GPAC video

player which are both licensed under LGPL. The open HEVC decoder supports the Main profile

of HEVC and can decode 1080p at 30 fps video using a single core CPU. On October 29, 2014)

second approved version of the HEVC/H.265 standard which adds 21 range extensions profiles,

two scalable extensions profiles, and one multi-view extensions profile

4.1.3 Version 3: (April 29, 2015) third approved version of the HEVC/H.265 standard which

adds the 3D Main profile

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4.2 HEVC ENCODER AND DECODER[7]:

Figure # 3 BLOCK DIAGRAM OF HEVC ENCODER [3]

Source video consisting of a sequence of video frames is encoded or compressed by a video

encoder to create a compressed video bit stream. The compressed bit-stream is stored or

transmitted. A video decoder decompresses the bit stream to create a sequence of decoded

frames represent the steps followed by encoder and decoder.

4.2.1 ENCODER AND ITS STEPS:

The video encoder performs the following steps:

1. Partitioning each picture into multiple units

2. Predicting each unit using inter or intra-prediction, and subtracting the prediction from

the unit

3. Transforming and quantizing the residual (the difference between the original picture unit

and prediction)

4. Entropy encoding transform output, prediction information, mode information and

headers

4.2.2 DECODER AND ITS STEPS:

The video decoder performs the following steps:

1. Entropy decoding and extracting the elements of the coded sequence

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2. Rescaling and inverting the transform stage

3. Predicting each unit and adding the prediction to the output of the inverse transform

4. Reconstructing a decoded video image.

4.3 FEATURES

HEVC was designed to improve coding efficiency compared to H.264/MPEG-4 AVC HP, i.e. to

reduce bit-rate requirements by half with comparable image quality, at the expense of increased

computational complexity[7]. HEVC was designed with the goal of allowing video content to

have a data compression ratio of up to 1000:1 [3]. Depending on the application requirements,

HEVC encoders can trade off computational complexity, compression rate, robustness to errors,

and encoding delay time. Two of the key features where HEVC was improved compared to

H.264/MPEG-4 AVC was support for higher resolution video and improved parallel processing

methods.

HEVC is targeted at next-generation HDTV displays and content capture systems which feature

progressive scanned frame rates and display resolutions from QVGA (320x240) to 4320p

(7680x4320), as well as improved picture quality in terms of noise level, color spaces, and

dynamic range[1].

HEVC was designed with the idea that progressive scan video would be used and no coding tools

were added specifically for interlaced video. Interlace specific coding tools, such as MBAFF and

PAFF, are not supported in HEVC [4]. HEVC instead sends metadata that tells how the

interlaced video was sent. Interlaced video may be sent either by coding each frame as a separate

picture or by coding each field as a separate picture. For interlaced video HEVC can change

between frame coding and field coding using Sequence Adaptive Frame Field (SAFF), which

allows the coding mode to be changed for each video sequence.This allows interlaced video to be

sent with HEVC without needing special interlaced decoding processes to be added to HEVC

decoders.

4.3.1 Image Partitioning: The previous standards split the pictures in block-shaped regions

called Macro-blocks and Blocks. In HEVC, we have high-resolution video content, so the use of

variable block sizes is advantageous for encoding. To support this wide variety of blocks size in

efficient manner HEVC pictures are divided into so-called coding tree Units (CTUs).CTU

actually divide the image into CU(Coding Units) which in turn are divided into PU(Partition

Units) depending upon the requirement to encode. Depending on the stream parameters, the

CTUs in a video sequence can have the size: 64×64, 32×32, or 16×16.

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4.3.2 A PICTURE REPRESENTINGCTU,CU,PU [2].

Figure # 4: A TREE DIAGRAM FOR CTU,CU,PU [2]

Coding Tree Unit (CTU) is therefore a coding unit, which is in turn encoded into an HEVC bit-

stream. It consists of three blocks, namely luma (Y), that covers a square picture area of LxL

samples of the luma component, and two chroma components (Cb and Cr), that cover L/2xL/2

samples of each of the two chroma components, and associated syntax elements, Each block is

called Coding Tree Block (CTB).

Syntax elements describe properties of different types of units of a coded block of pixels and

how the video sequence can be reconstructed at the decoder. This includes the method of

prediction (e.g. inter or intra prediction, intra prediction mode, and motion vectors) and other

parameters.

4.3.3 Coding efficiency [3]:

The design of most video coding standards is primarily aimed at having the highest coding

efficiency. Coding efficiency is the ability to encode video at the lowest possible bit rate while

maintaining a certain level of video quality. There are two standard ways to measure the coding

efficiency of a video coding standard, which are to use an objective metric, such as peak signal-

to-noise ratio (PSNR), or to use subjective assessment of video quality. Subjective assessment of

video quality is considered to be the most important way to measure a video coding standard

since humans perceive video quality subjectively.

HEVC benefits from the use of larger coding tree unit (CTU) sizes. This has been shown in

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PSNR tests with a HM-8.0 HEVC encoder where it was forced to use progressively smaller CTU

sizes. For all test sequences, when compared to a 64×64 CTU size, it was shown that the HEVC

bit rate increased by 2.2% when forced to use a 32×32 CTU size, and increased by 11.0% when

forced to use a 16×16 CTU size. In the Class A test sequences, where the resolution of the video

was 2560×1600, when compared to a 64×64 CTU size, it was shown that the HEVC bit rate

increased by 5.7% when forced to use a 32×32 CTU size, and increased by 28.2% when forced

to use a 16×16 CTU size. The tests showed that large CTU sizes increase coding efficiency while

also reducing decoding time.

4.3.4 Coding tools:

4.3.4.1 Coding tree unit:

HEVC replaces 16×16 pixel macro-blocks, which were used with past stages, with coding tree

units (CTUs) which can use greater square structures of up to 64x64 samples and can better sub-

allocate photograph into variable measured structures. HEVC at first divides the picture into

CTUs which can be 64×64, 32×32, or 16×16 with a larger pixel bit size regularly improving the

coding effectiveness.[9]

4.3.4.2 Parallel handling tools:

Tiles allow for the picture to be divided into a grid of rectangular regions that can independently

be decoded/encoded[10]. The main purpose of tiles is to allow for parallel processing. Tiles can

be independently decoded and can even allow for random access to specific regions of a picture

in a video stream.

4.3.4.3 Wavefront parallel processing (WPP)[9]:It is implemented when a slice is divided into

rows of CTUs in which the first row is decoded normally but each additional row requires that

decisions be made in the previous row WPP has the entropy encoder use information from the

preceding row of CTUs and allows for a method of parallel processing that may allow for better

compression than tiles.

Tiles and WPP are allowed, but are optional. If tiles are present, they must be at least 64 pixels

high and 256 pixels wide with a level specific limit on the number of tiles allowed.

Slices can, for the most part, be decoded independently from each other with the main purpose of

tiles being the re-synchronization in case of data loss in the video stream.

Slices can be defined as self-contained in that prediction is not made across slice boundaries.

When in-loop filtering is done on a picture though, information across slice boundaries may be

required. Slices are CTUs decoded in the order of the raster scan, and different coding types can

be used for slices such as I types, P types, or B types.

Dependent slices can allow for data related to tiles or WPP to be accessed more quickly by the

system than if the entire slice had to be decoded. The main purpose of dependent slices is to

allow for low-delay video encoding due to its lower latency.because in flat areas which are prone

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to banding artifacts, sample amplitudes tend to be clustered in a small range. The SAO filter was

designed to increase picture quality, reduce banding artifacts, and reduce ringing artifacts.

4.4 CABAC & IT’S OVERVIEW[7]:

Context-adaptive binary arithmetic coding (CABAC) is a form of entropy encoding used in

the H.264/MPEG-4 AVC and High Efficiency Video Coding (HEVC) standards .It is a well

known bottleneck in AVC/H.264 [8]. It is a lossless compression technique, although the video

coding standards in which it is used are typically for lossy compression applications. CABAC is

notable for providing much better compression than most other entropy encoding algorithms

used in video encoding, and it is one of the key elements that provides the H.264/AVC encoding

scheme with better compression capability than its previous standards. CABAC has multiple

probability modes for different contexts. It first converts all non-binary symbols to binary. Then,

for each bit, the coder selects which probability model to use, then uses information from nearby

elements to optimize the probability estimate. Arithmetic coding is finally applied to compress

the data.

In H.264/MPEG-4 AVC, CABAC is only supported in the Main and higher profiles of the

standard, as it requires a larger amount of processing to decode than the simpler scheme known

as context-adaptive variable-length coding (CAVLC) that is used in the standard is Baseline

profile. CABAC is also difficult to parallelize and vectorize, so other forms of parallelism may

be coupled with its use. In HEVC, CABAC is used in all profiles of the standard.

4.4.1 CABAC ALGORITHM[9]:

CABAC is based on arithmetic coding, with a few innovations and changes to adapt it to the

needs of video encoding standards.

1. It encodes binary symbols, which keeps the complexity low and allows probability

modeling for more frequently used bits of any symbol.

2. The probability models are selected adaptively based on local context, allowing better

modeling of probabilities, because coding modes are usually locally well correlated.

3. It uses a multiplication-free range division by the use of quantized probability ranges and

probability states.

4.5 HEVC CABAC & its main steps[1]

4.5.1.Binarization: Syntax elements are mapped to binary symbols (bins) using a

binarization process. Various forms of binarization are used in AVC and HEVC (e.g. Exp-

Golomb, fixed length, truncated unary, custom). Combinations of different binarizations are also

allowed where the prefix and suffix are binarized differently. For example, the prefix can be

truncated unary and the suffix can be fixed length (this combination is also called as truncated

rice). Alternatively, truncated unary can be used for the prefix, and Exp-Golomb for the suffix.

The standard defines which type of binarization is used for each syntax element.

.

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4.5.2. Arithmetic Coding:

The bins are compressed into bits using arithmetic coding . Multiple bins can be represented by a

single bit. This allows syntax elements to be represented by a fractional number of bits, which

improves coding efficiency. Arithmetic coding involves recursive sub-interval division, where a

range is divided into two subintervals based on the probability of the symbol that is being

compressed. The encoded bits represent an offset that, when converted to a binary fraction,

selects one of the two subintervals, which indicates the value of the decoded bin. After every

decoded bin, the range is updated to equal the selected subinterval, and the interval division

process repeats itself. In order to effectively compress the bins to bits, the probability of the bins

must be accurately estimated.

4.5.3. Context Selection: The context modeling and selection is used to accurately

model the probability of each bin. The probability of the bin depends on the type of

syntax element it belongs to, the bin index within the syntax element ,it can be most

significant bin or least significant bin and the properties of spatially neighboring

coding units. There are several hundred different context models used in AVC and

HEVC. As a result, a large finite state machine is needed to select the correct context

for each bin. In addition, the estimated probability of the selected context model is

updated after each binary symbol is encoded or decoded.[8]

At the decoder, there are several feedback loops in the CABAC . The context and

probability of the next bin depends on the decoded value of the current bin; the

current bin determines the bin index and syntax element and consequently the

context of the next bin. This bin-to-bin dependency makes it difficult to process

multiple bins in a parallel manner. The context and probability for the next bin can

be determined to increase concurrency; however, due to the complexity of the

context selection finite state machine, these operations are expensive in terms of

power and area, and grow exponentially as the number of bins increases. The context

update and range update feedback loops are simpler than the context selection loops

and thus do not affect throughput as severely. Not all bins are coded using an

estimated probability it can be context coded.[11]

Bins can also be coded assuming equal probability of 0.5 also known as bypass

coded. As a result, bypass coded bins avoid the feedback loop for the context

selection. In addition, the arithmetic coding is also simpler and faster for bypass

coded bins, as the division of the range into subintervals can be done by a shift,

rather than a look up table which is required for the context coded bins. Thus

multiple bypass bins can be processed concurrently in the same cycle at lower power

and area cost than context coded bins.[12]

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Figure # 8: BLOCK DIAGRAM OF CABAC [8]

4.6 CABAC ENCODER:

Figure # 9 A BLOCK DIAGRAM OF CABAC ENCODER [11]

4.7 The arithmetic decoding procedure[10]:

4.7.1.Probability estimation is performed by a transition process between 64 separate probability

states for "Least Probable Symbol" LPS, the least probable of the two binary decisions "0" or "1"

4.7.2.The range R representing the current state of the arithmetic coder is quantized to a small

range of pre-set values before calculating the new range at each step, making it possible to

calculate the new range using a look-up table (i.e. multiplication-free).

4.7.3.A simplified encoding and decoding process is defined for data symbols with a near

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uniform probability distribution.

The definition of the decoding process is designed to facilitate low-complexity implementations

of arithmetic encoding and decoding. Overall, CABAC provides improved coding efficiency

compared with CAVLC-based coding, at the expense of greater computational complexity.

4.8) THROUGHPUT IMPROVEMENTS CABAC

In HEVC, the binarization and context selection of CABAC were modified, while the arithmetic

coding engine remained the same as AVC. This section highlights three techniques that were

used to improve the throughput of CABAC in HEVC[7]. We evaluate the performance of this

HEVC against AVC with a new metric called Bjntegaard delta cycles(BD-Cycles) .BD-cycle

uses the Bjntegaard delta measurement method to compute the average difference between the

cycles vs. bit-rate curves of HEVC and AVC and thereby ,CABAC throughput versus the AVC.

Enabling higher throughput is desirable since it can be used to support higher pixel rates for

higher resolutions and frame rates and throughput can also be traded off for reduced power

consumption with the help of voltage scaling. Parallel processing is an effective way to increase

throughput. However, this is challenging as the purpose of video compression is to remove

redundancy which introduces dependency and makes parallelism difficult.

4.8.1) Reduce total number of bins :In here ,the binarization of the coefficient

level was modified to reduce the total number of bins. The coefficient levels account

for a significant portion on average 15 to 25% of the total number of bins. While

AVC uses truncated unary prefix followed by an Exp-Golomb suffix, HEVC uses a

truncated unary prefix followed by fixed length suffix. This combination is also

known as truncated rice. Up to the value of 12 coefficients HEVC and AVC have the

same number of bins however, for coefficient values above 12, the binarization

process used in HEVC always results in fewer bins than AVC[6][7][9][4]. The

transition point between the prefix and suffix was set such that the maximum total

number of bins for coefficient level 12 was reduced from 43 to 34 . The maximum

total number of bins for delta QP was also reduced from 53 to 15 by using truncated

unary plus Exp-Golomb rather than unary, and signaling the sign value separately .

for a worst case scenario of 16x16 block of pixels, total number of bins was reduced

in HEVC by 1.5x compared to AVC.

4.8.2) Reduce number of context coded bins: The number of context coded

bins was significantly reduced for syntax elements such as motion vectors and

coefficient levels. For these syntax elements, the first few bins were context coded,

and the remaining bins were bypass coded. For instance, in AVC, the first 9bins of

the motion vector difference were context coded. For HEVC, it was determined that

only the first two bins had to be context coded. Similarly, the number of context

coded bins for each coefficient level was reduced from 14 in AVC to either 1 or 2

19

(depending on the number of coefficients per 4x4 block) in HEVC .Table 1

summarizes the reduction in context coded bins for various syntax elements. Overall,

if we calculate of the number of times each syntax element appears for a 16x16 block

of pixels, the worst case scenario of context coded bins was reduced by over 8x

compared to AVC.

TABLE #1 : SYNTAX ELEMENTS FOR WHICH THE CONTEXT CODING IS

DONE. [12]

4.8.3 Grouping of bypass bins: Due to the effort to reduce the number of context

coded bins, bypass bins account for a significant portion of the total bins in HEVC.

As a result, processing multiple bypass bins per cycle can significantly increase the

overall CABAC throughput. Multiple bypass bins can only be processed in the same

cycle if bypass bins appear consecutively in the bin stream [3][10][9][7]. Thus long

runs of bypass bins result in higher throughput than frequent switching between

bypass and context coded bins. Accordingly, bypass bins were grouped together

across multiple syntax elements to maximize the run length of bypass bins. For

instance, the sign bins of the different coefficients were grouped together and the

bypass portion of the coefficient levels were grouped together. Table 2 summarizes

the syntax elements where bypass grouping was used.

TABLE # 2: SYNTAX ELEMENTS FOR WHICH BYPASS PROCESS IS

FOLLOWED [11]

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The entropy coding procedure utilized within video coding will be the:. - Context-Based

Adaptive Binary Arithmetic Coding(CABAC) .CABAC outperforms other entropy encoders As

far as coding effectiveness. Entropy coding for HEVC will be In light of CABAC algorithm.[7]

HEVC technology is based on hybrid coding scheme with motion-compensated prediction,

transform coding & entropy coding of residual data. The HEVC utilizes new coding structure by

introducing coding Unit(CU), Prediction Unit(PU), and transform Unit(TU) which Perform

prediction & adaptive coding of information to pieces of numerous size[1]:.

CU Size- 64x64 to 8x8. PU Size- 8x4 alternately 4x8. TU Size-4x4 up to 32x32(Square)

alternately 32x8,8x32,16x4,4x16(Non-Square). The new coding structures allows choosing the

size of block for prediction & transform in an adaptive manner exploiting local features of an

image.

The HEVC feature compression technology utilizes Context based Adaptive Binary Arithmetic

Coding(CABAC) entropy. which may be an altered version of CABAC encoder that is utilized

within MPEG-4 AVC/H. 26 feature video compression standard

Figure # 10 BLOCK DIAGRAM OF CABAC [12] The different characteristic of CABAC algorithm will be provision the binary arithmetic codec

core that is able to encode binary symbols

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225 models would be characterized over CABAC with HEVC.

CABAC introduces two fundamental simplifications in place will accelerate computations: -

Probabilities from symbols are computed to a rearranged best approach utilizing pre-defined

finite state Machine (FSM) for 64 States.

-Some images are encoded in the purported bypass coding produced for no information modeling

stage.

Simplifications settled on On CABAC setting modeler piece essentially lessens precision of

image probabilities which. Negatively influences compression execution.

Main idea of improved CABAC uses more accurate mechanism of data statistics estimation

relative to original algorithm.

In the improved CABAC, the CTW method is used by every statistical model to calculate

conditional probability of symbol more accurately

• Application of the improved CABAC within HEVC increases compression performance

of video encoder.

• As seen in the table below an average of 2.6% bit rate reduction was obtained for used

video sequences

IMPROVED CABAC VER 2 BLOCK DIAGRAM

Figure # 11 IMPROVED VERSION OF CABAC [8]

Compression performance of future HEVC technology can be further expanded when utilizing

enhanced entropy of the encoder.

22

Better information measurements estimation in CABAC gives 1.6% - 4.5% diminishment of

HEVC bit-stream

5 CONCLUSION:

The throughput was measured for 24 video sequences of various resolutions that were used by

JCT-VC during the HEVC standardization process. These sequences were encoded with HM-8.0

reference software for HEVC [13] and JM-18.4 reference software for AVC. The HM-8.0

encoder was configured based on the common conditions set by JCT-VCb [9][10]. Under the

common condition, for both AVC and HEVC, 12 encoded bit-streams are generated for each of

the 24 video sequences, which covers four quantization points QP = 22, 27, 32, 37and three

different configuration.

Graph # 1 PSNR vs BIT RATE COMPARISON OF HEVC AND AVC [8]

Table # 3 BIT RATE COMPARISON OF VERSIONS OF CABAC [8]

23

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24

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