PROJECT FINAL REPORT

STUDY OF HEVC DEBLOCKING FILTER AND ITS IMPLIMENTATION

EE 5359

Under the guidance of DR. K.R RAO

RAKESH SAI SRIRAMBHATLA (1000869391)

rakeshsai.srirambhatla@mavs.uta.edu

ACKNOWLEDGEMENT

I am highly indebted to Dr. K. R. Rao for his guidance and constant supervision as well as for providing necessary information regarding the project and also for his support in completing the project.

My thanks and appreciations also go to my classmates in helping for the project and people who have willingly helped me out with their abilities.

LIST OF ACRONYMS

AVC Advanced Video Coding

ALF Adaptive loop filter

B Bi-predictive

BO Band offset

CB Coding Block

DBF Deblocking filter

CSVT Circuits and Systems for Video Technology

CTB Coding Tree Block

CTU Coding Tree Unit

CU Coding Unit

EO Edge offset

GOP Group of pictures

HEVC High Efficiency Video Coding

I Intra frame

ISO International Standardization Organization

ITU-T International Telecommunication Union - Telecommunication Standardization Sector

JCT-VC Joint Collaborative Team on Video Coding

LCU – Largest coding unit

MPEG Moving Picture Experts Group

MSE – Mean square error

PB Prediction Block

PSNR – Peak signal to noise ratio

QP – Quantization parameter

SAO – Sample adaptive offset

SNR – Signal to noise ratio

SPS – Sequence parameter set

TB Transform Block

TU Transform Unit

VCEG Video Coding Experts Group

Scope of the project:

High Efficiency Video Coding (HEVC) is currently being prepared as the newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The main goal of the HEVC standardization effort is to enable significantly improved compression performance relative to existing standards—in the range of 50% bit-rate reduction for equal perceptual video quality.[2] Scope of this project is to primarily focus on the study of in-loop deblocking filter in HEVC. Besides this study, performance comparison is done between HEVC and H.264 deblocking filter.

H.264/Advanced video coding (AVC) Standard overview:

Video sequence is partitioned into multiple groups of pictures. Each group of pictures (GOP) is then partitioned into a number of frames. Hierarchy is

shown in the figure 1.

Figure 1Video sequence partitioning structure [7]

In the figure 1, each GOP is partitioned into frames namely IBBPP. Figure 2 shows an example of group of pictures in a specific frame pattern.

I- frame : Intra coded, P-frame: Predictive picture, B: Bi predictive picture Every frame is then partitioned into a set of slices. Slices are subparts of a frame for

which specific data structure is defined.

Figure 2

Example of group of pictures (GOP) structure [8]

Slices (Frames) are comprised of macro-blocks. Group of individual non-overlapping blocks account to one macro-block.

Slices and macro-blocks partitioning structure is shown in figure 3.

Figure 3Slice portioning in video coding [7]

In the figure 3 each slice is partitioned into macro-blocks. Macro blocks are then partitioned into blocks namely 1, 2, 3…N as shown in figure 3.

Each macro-block is a set of individual boxes. In the initial standards each block size used to be 8x8.

Features of H.264 video coding standard :

Variable block size motion compensation with small block sizes. This standard supports more flexibility in the selection of motion compensation block sizes and shapes than any previous standards.[2]

Quarter sample accurate motion compensation. Previous standards support half sample motion vector accuracy. H.264 standard has an improvement over previous standards by adding quarter sample motion vector accuracy.[2]

Motion vectors over picture boundaries. Picture boundary exploitation is included in H.264 standard.[2]

Small block size transformation. In this video coding standard, all major prior video coding standards used a transform block size of 8 8, while H.264/AVC design is based primarily on a 4x4 transform. This allows the encoder to represent signals in a more locally-adaptive fashion, which reduces artifacts known colloquially as “ringing”. [2]

Evolution of video coding standards:

Figure 4 shows the historical evolution of video coding standards since the very first ITU-T (International Telecommunication Union - Telecommunication Standardization Sector) H.120 to the very latest HEVC.

Figure 4Generations of video coding standards [10]

High efficiency video coding overview:

HEVC is the advanced video compression format or algorithm and successor of H.264 encoding format which is being used in the blu-ray discs.

Significant development in HEVC is its data compression ratio which is double the AVC/ H.264. 50% bitrate reduction for equal perceptual video quality. [1]

Joint collaborative team on video coding (JCT-VC) developed HEVC video coding standard. JCT-VC is a joint partnership team between video coding experts group (VCEG) and moving picture experts group (MPEG).

As HEVC is the direct successor for H.264, it contains all the applications of H.264. On the top of these applications, developments are made so as to increase video resolution and use of parallel processing architectures. [1]

HEVC has improvements in many aspects when compared to previous standards of video compression. Areas of improvements are partitioning. Partitioning in HEVC is

much more flexible than the previous standards. Flexibility in prediction modes is also higher when compared to previous standards. Prediction is much more sophisticated. Parallel processing is supported in a much more efficient way. Figure 5.a shows CTB (coding tree block) and its partitions. CTB (solid block) partitioned into CB (coding block) (solid) and transform blocks (dashed) of variable size. Figure 5.b shows the corresponding nested quadtree structure.

Figure 5.a CTB and its partitions [10] Figure 5.b Quadtree structure [10]

Initially a source consisting of sequence of video frames is compressed by a HEVC encoder and the output is a compressed video bitstream. This video bitstream is then fed into a decoder to obtain decoded frames.

Compared to H.264 and other previous standards, HEVC has the following improvements: 1.Partitioning is more flexible from large to small partitioning sizes 2. Higher flexibility in prediction modes and transform block sizes 3. Interpolation and deblocking filters, prediction and signaling of modes and motion vectors are much more sophisticated 4. Efficient parallel processing is supported. [5]

Block diagram of HEVC is given in figure 6.

Figure 6

Block Diagram of HEVC encoder [1]

Working of HEVC

Each picture is partitioned into multiple units. Next step corresponds to prediction. Prediction can be inter or intra prediction and

ultimately subtracting prediction from the unit. Transforming and quantizing the residual. Entropy encoding the transforming output, prediction information, mode information

and headers. Video encoder and decoder overall structure is given in figure 7.

Figure 7Structure of HEVC [5]

After encoding, next comes decoding the output from the encoder. Main targets of HEVC are at same picture size and quality, an HEVC video sequence

should occupy less storage capacity. [5] At the same storage bandwidth, quality and resolution has to be higher than H.264

encoder.[5]

Deblocking filter and its working

In HEVC, two processing steps, namely a deblocking filter (DBF) followed by an SAO filter, are applied to the reconstructed samples before writing them into the decoded picture buffer in the decoder loop. The DBF is intended to reduce the blocking artifacts due to block-based coding. The DBF is similar to the DBF of the H.264/MPEG-4 AVC standard, whereas SAO is newly introduced in HEVC. While the DBF is only applied to the samples located at block boundaries, the SAO filter is applied adaptively to all samples satisfying certain conditions. During the development of HEVC, it had also been considered to operate a third processing step called the adaptive loop filter (ALF) after the SAO filter; however, the ALF feature was not included in the final design.[1]

A deblocking filter similar to the one used in H.264/MPEG-4 AVC is operated within the interpicture prediction loop. However, the design is simplified in regard to its decision-making and filtering processes, and is made more friendly to parallel processing. [1]

The deblocking filter in HEVC has been designed to improve the subjective quality while reducing the complexity. The latter consideration is important since the deblocking filterof the H.264/AVC standard [11], [13] constitutes a significant part of the decoder complexity. As a result, the HEVC deblocking filter is less complex as compared to the H.264/AVC deblocking filter, while still having the capability to improve the subjective and objective qualities. Another aspect that received significant attention in the HEVC deblocking filter design is its suitability for parallel processing. Deblocking in HEVC has been designed in a way to prevent spatial dependences across the picture, which, together with other design features, enables easy parallelization on multiple cores.

The deblocking filter is applied to all samples adjacent to a PU or TU boundary except the case when the boundary is also a picture boundary, or when deblocking is disabled across slice or tile boundaries (which is an option that can be signaled by the encoder) as shown in figure 8. It should be noted that both PU and TU boundaries should be considered since PU boundaries are not always aligned with TU boundaries in some cases of interpicture-predicted CBs. Syntax elements in the SPS and slice headers control whether the deblocking filter is applied across the slice and tile boundaries. [1]

Figure 8 Schematic showing the edges of PU, TU and picture boundary [11]

Unlike H.264/MPEG-4 AVC, where the deblocking filter is applied on a 4×4 sample grid basis, HEVC only applies the deblocking filter to the edges that are aligned on an 8×8 sample grid, for both the luma and chroma samples. This restriction reduces the worst-case computational complexity without noticeable degradation of the visual quality. It also improves parallel-processing operation by preventing cascading interactions between nearby filtering operations.

The strength of the deblocking filter is controlled by the values of several syntax elements similar to the scheme in H.264/MPEG-4 AVC, but only three strengths are used rather than five. Given that P and Q are two adjacent blocks with a common 8×8 grid boundary, the filter strength of 2 is assigned when one of the blocks is intrapicture predicted. Otherwise, the filter strength of 1 is assigned if any of the following conditions is satisfied.[1]

1) P or Q has at least one nonzero transform coefficient.[1]2) The reference indices of P and Q are not equal.[1]3) The motion vectors of P and Q are not equal.[1]4) The difference between a motion vector component of P and Q is greater than or equal to one integer sample. [1]

If none of the above conditions is met, the filter strength of 0 is assigned, which means that the deblocking process is not applied. According to the filter strength and the average quantization parameter of P and Q, two thresholds, tC and β, are determined from predefined tables. For luma samples, one of three cases, no filtering, strong filtering, and weak filtering, is chosen based on β. Note that this decision is shared across four luma rows or columns using the first and the last rows or columns to reduce the computational complexity. There are only two cases, no filtering and normal filtering, for chroma samples. Normal filtering is applied only when the filter strength is greater than one. The filtering process is then performed using the control variables tC and β. Figure 9 shows an example for filtering decision of vertical edge and pixel samples.[1]

Figure 9Filtering decision example for HEVC [11]

In HEVC, the processing order of the deblocking filter is defined as horizontal filtering for vertical edges for the entire picture first, followed by vertical filtering for horizontal edges. This specific order enables either multiple horizontal filtering or vertical filtering processes to be applied in parallel threads, or can still be implemented on a CTB-by-CTB basis with onlya small processing latency. Figure 10 shows the detailed filtering process.

Figure 10Deblocking filtering procedure in HEVC[11]

As per the basic ordering principle of HEVC, the right most horizontal edges in the current LCU could not be processed before the leftmost vertical edges of next LCU is processed. For example in figure 4 the filtering on edge 21 and 22 will be done after edge 17 through 20 is completed. From the time slot it is easy to see that the filtering for #n+1, #n and #n-1 LCU is not sequential but alternative, which introduce 3 drawbacks as explained below:

(a) The control of the filtering is complex and the hardware cost in control part is large. Usually, the control part cost is larger than the filtering computational part, so the control complexity is very critical for the hardware design. (b) The filtering of one LCU involves the data from left, right and upper neighboring LCUs. The cost of buffers or memory accesses will be increased. (c) There is latency in the process of current LCU. In other words, the filtering of current LCU cannot be completed before the data of next LCU is available. This will decrease the throughput of the whole decoding system.

Unified cross based approach

A novel processing order is proposed in [11] by Li et al where the blocks are chosen and combined to form a processing unit which is shown in figure 11. This is termed as unified-cross unit which is different from LCU. This unit is symmetric and the edges need to be filtered are arranged in several crosses. The benefit of this approach is that the unified-cross units are independent with each other. The processing order for the unified-cross unit is shown in figure 11. The advantages of implementing the unified-cross based processing is it can implement the parallel processing in true sense which results in decreased computing time and less hardware requirements.

Figure 11Unified cross based processing[11]

Low Complexity Deblocking Filter Perceptual Optimization For The HEVC [12]

The perceptual optimization is performed by varying the two aforementioned offsets to minimize a Generalized Block-edge Impairment Metric (GBIM), taken as good quality metric to quantify the blocking artifacts visibility. The proposed novelty may be summarized in two main contributions: first, the GBIM is extended to consider the new block sizes considered in the TMuC codec and, second, a low complexity deblocking filter offsets perceptual optimization is

proposed to improve the GBIM quality while significantly reducing the computational resources that would be required by a brute force approach where all possible offset values would be exhaustively tested. The proposed deblocking filter offsets perceptual optimization is parameterized to become a dynamic, tuneable tool able to provide some additional video quality at the cost of some low computational complexity increase at both the encoder and decoder sides since the deblocking filter is in the coding loop. To the best of the authors’ knowledge, there is no proposal in the literature for a perceptual optimization of the deblocking filter, notably by varying the deblocking filter offsets of the H.264/AVC standard.[12]

The proposed GBIM extension comprises of two terms: (i) perceptually weighted block edge pixel difference, Mh (Mv) which basically represents the norm of the horizontal (or vertical) block edge pixel differences, weighted by the perceptual weight wp. (ii) Perceptually weighted non block edge average difference, Eh (Ev) which represents the norm of the average for those pixels between horizontal (or vertical) block edges. The frame level GBIM f is calculated by using (a) [12].

(a) GBIM equation [12]

Sample adaptive offset (SAO) filter

A nonlinear amplitude mapping is introduced within the interpicture prediction loop after the deblocking filter. Its goal is to better reconstruct the original signal amplitudes by using a look up table that is described by a few additional parameters that can be determined by histogram analysis at the encoder side. [25]

While the DBF is only applied to the samples located at block boundaries, the SAO filter is applied adaptively to all samples satisfying certain conditions, e.g., based on gradient. During the development of HEVC, it had also been considered to operate a third processing step called the adaptive loop filter (ALF) after the SAO filter; however, the ALF feature was not included in the final design. [25]SAO is located after DF and also belongs to in-loop filtering. The concept of SAO is to reduce mean sample distortion of a region by first classifying the region samples into multiple categories with a selected classifier, obtaining an offset for each category, and then adding the offset to each sample of the category, where the classifier index and the offsets of the region are coded in the bitstream. [25] A customized SAO encoder does not necessarily attempt to minimize mean sample distortion but can use another criterion to generate SAO parameters. SAO not only is useful in HEVC but also can be applied on top of AVC and other prior video coding standards. [25]

SAO may use different offsets sample by sample in a region depending on the sample classification, and SAO parameters are adapted from region to region. Two SAO types that can satisfy the requirements of low complexity are adopted in HEVC: edge offset (EO) and band offset (BO). For EO, the sample classification is based on comparison between current samples and neighboring samples. For BO, the sample classification is based on sample values. Please note that each color component may have its own SAO parameters. To achieve low encoding latency and to reduce the buffer requirement, the region size is fixed to one CTB. To reduce side information, multiple CTUs can be merged together to share SAO parameters. [25]

Figure 11 [25]Four 1-D directional patterns for EO sample classification: horizontal(EO class = 0), vertical (EO class = 1), 135° diagonal (EO class = 2), and

45° diagonal (EO class = 3). [25]

Figure 12 [25]Positive offsets for EO categories 1 and 2 and negative offsets for

EO categories 3 and 4 result in smoothing.

Test Sequences

Basketball.yuv [19]Picture of test sequence Basketball.yuv with resolution 832×480 with the frame rate = 50 frames/sec.

Figure 13 [19]BQMall.yuv [19]Picture of test sequence BQmall.yuv with resolution 832×480 with the frame rate = 60 frames/sec.

Figure 14 [19]

BQsquare.yuv [19]Picture of test sequence BQsquare.yuv with resolution 416×240 with the frame rate =60 frames/sec.

Figure 15 [19]

Kirsten&Sara.yuv [19] Picture of test sequence Kirsten&Sara.yuv with resolution 1280×720 with the frame rate = 60 frames/sec.

Figure 16 [19]

Implementation

Test sequence and test environment details• In the initial implementation, Kirsten&Sara.yuv [19] is considered as the test sequence.• Picture of test sequence Kirsten&Sara.yuv [19] with resolution 1280×720 with the frame

rate = 60 frames/sec.• Total of 10 frames are considered for the test.• HM.13 HEVC codec software [20] has been used for execution of the test.• All the test sequences are implemented using HM main profile configuration. • In the final report the same test cases are run for four different sequences.

Deblocking filter implementation • Enable/Disable Deblocking Filter [24]• LoopFilterDisable parameter – under Deblock Filter – alone would not do the job of

disabling the deblocking filter [24] • Have to use combination of following deblocking filter parameters: [24]

DeblockingFilterControlPresentLoopFilterDisableLoopFilterBetaOffset_div2 LoopFilterTcOffset_div2

Metrics for the test

• PSNR is plotted for all the test sequences for different quantization parameters.

[1]

• Total encoding time is plotted for all the test sequences for different quantization parameters.

• Bitrate is also plotted for all the test sequence for different quantization parameters.

Results and observations

Tables

Kristen and Sara.yuvResolution: 1280×720Frame rate: 60 frames /secNumber of frames for the test: 20

Kristen & Sara.yuvBefore enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 11678.456 Kbps 291.401 secs 41.59 dB

QP = 32 7875.744 Kbps 252.133 secs 39.68 dB

QP = 34 6502.744 Kbps 241.544 secs 38.77 dB

Table 1.aMetrics before enabling the deblocking filter.

Kristen & Sara.yuvAfter enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 11694.4 Kbps 302.625 secs 42.28 dB

QP = 32 7890.7 Kbps 264.625 secs 40.41 dB

QP = 34 6587.7 Kbps 249.845 secs 39.82 dB

Table 1.bMetrics after enabling the deblocking filter.

Basket Ball.yuvResolution: 832×480Frame rate: 60 frames /secNumber of frames for the test: 20

Basket ball.yuvBefore enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 9856 Kbps 152.344 secs 38.45 dB

QP = 32 5878 Kbps 136.465 secs 35.90 dB

QP = 34 4580 Kbps 131.412 secs 35.01 dB

Table 2.aMetrics before enabling the deblocking filter.

Basket ball.yuvAfter enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 9887 Kbps 160.767 secs 39.32 dB

QP = 32 5902 Kbps 144.879 secs 36.72 dB

QP = 34 4609 Kbps 138.151 secs 35.89 dB

Table 2.bMetrics after enabling the deblocking filter.

BQ Square.yuvResolution: 416×240Frame rate: 60 frames /secNumber of frames for the test: 20

BQ Square.yuvBefore enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 7650 Kbps 52.657 secs 37.38 dB

QP = 32 5240 Kbps 45.898 secs 34.84 dB

QP = 34 4489 Kbps 37.267 secs 32.88 dB

Table 3.aMetrics before enabling the deblocking filter.

BQ Square.yuvAfter enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 7715 Kbps 60.774 secs 38.89 dB

QP = 32 5313 Kbps 56.156 secs 35.99 dB

QP = 34 4503 Kbps 45.856 secs 33.90 dB

Table 3.bMetrics after enabling the deblocking filter.

BQ Mall.yuvResolution: 832×480Frame rate: 60 frames /secNumber of frames for the test: 20

BQ Mall.yuvBefore enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 15788 Kbps 157.24 secs 34.90 dB

QP = 32 9925 Kbps 151.65 secs 36.26 dB

QP = 34 8567 Kbps 135.774 secs 33.90 dB

Table 4.aMetrics before enabling the deblocking filter.

BQ Mall.yuvAfter enabling deblocking filter

Bitrate ComputationalTime

PSNR

QP = 28 15850 Kbps 167.989 secs 34.90 dB

QP = 32 10408 Kbps 164.879 secs 36.26 dB

QP = 34 8790 Kbps 144.151 secs 33.90 dB

Table 4.bMetrics before enabling the deblocking filter.

Computational time (in seconds) for four test sequences

PSNR (in dB) for four test sequences

Bitrate (in Kbps) for four test sequences [26]

Conclusion

• The computational time for the test sequence has increased for all test sequences after the application of deblocking filter to the HEVC. Increase in the computational time is mainly because of the addition of deblocking filter since it increases the complexity of encoding the test sequence but gives a better picture quality.

• Though there is an increase in the computational time, main advantage of application of deblocking filter are better PSNR on the cost of bitrate on the other side. For all the test sequences PSNR was increased significantly which results in better picture quality of the test sequences.

Future work

• Performance optimization of deblocking filter and comparison of HEVC deblocking filter performance with the latter standards such as H.264.

REFERENCES:

[1] G.J Sullivan et al, “Overview of the H.264/AVC Video Coding Standard”, IEEE Trans. CSVT, vol.13, pp. 560-576, July 2003

[2] G.J. Sullivan et al, “Overview of the high efficiency video coding (HEVC) standard”, IEEE Trans. CSVT, vol.22, pp. 1649-1668, Dec 2012

[3] G.J. Sullivan et al, “Standardized extensions of High Efficiency Video Coding (HEVC)”, IEEE Journal Selected topics in signal processing, vol. 7, pp. 1001-1016, Dec 2013

[4] G.J. Sullivan et al, “Comparison of the Coding Efficiency of Video Coding Standards-Including High Efficiency Video Coding (HEVC)”, IEEE Trans. CSVT, Vol. 22, pp. 1669-1684, Dec 2012

[5] http://www.vcodex.com/images/uploaded/342512928230717.pdf , URL for document on introduction to HEVC

[6 ] http://en.wikipedia.org/wiki/Scalable_Video_Coding Wikipedia URL for scalable video coding which has the definitions of video coding standards.

[7 ] http://www.youtube.com/watch?v=f9n-7mgNsNQ URL for NPTEL video on basics of video coding standards.

[8] http://en.wikipedia.org/wiki/Inter_frame Wikipedia search URL for types of frames in video compression.

[10] N. Ling, “High efficiency video coding and its 3D extension: A research perspective," 7th IEEE Trans. on ICIEA, pp. 2150-2155, July 2012.

[11] M. Li et al, “De-blocking Filter Design for HEVC and H.264/AVC”, PCM 2012, Lecture Notes in Computer Science 7674, pp. 273–284, 2012.

[12] M. Naccari et al, “Low Complexity Deblocking Filter Perceptual Optimization For The HEVC Codec”, 18th IEEE International Conference on Image Processing, pp. 737-740, 2011.

[13] A. Norkin et al, “HEVC Deblocking Filter”, IEEE Trans. CSVT, Vol. 22, No. 12, pp. 1746-1754, Dec 2012.

[16] JM software download for H.264/AVC: http://iphome.hhi.de/suehring/tml/

[17] HM codec download for H.265: https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/branches

[18] HEVC standard test video sequences: ftp://ftp.tnt.uni-hannover.de/testsequences

[19] Test sequence source: http://media.xiph.org/video/derf/

[20] HEVC Reference Software HM13.0. https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/tags/HM-13.0rc1/

[21]10.2 JM H.264 software http://iphome.hhi.de/suehring/tml/

[22] JPEG2000 latest reference software (jasper version 1.900.0) Website: http://www.ece.uvic.ca/~mdadams/jasper/

[23] JM reference software, Fraunhofer institute for telecommunications Heinrich Hertz institute. http://iphome.hhi.de/suehring/tml/.

[24] HM reference software, Fraunhofer institute for telecommunications Heinrich hertz institute.http://hevc.hhi.fraunhofer.de/.

[25] C.M Fu et al, “Sample Adaptive Offset in the HEVC Standard”, IEEE Trans. CSVT, Vol.22, pp. 1755 – 1764, Dec 2012.

[27] PSNR reference http://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio

[28] BD bitrate reference Open source article, “Bit rate”. [Online]. Available: http://en.wikipedia.org/wiki/Bit_rate

[29] B. Bross et al, “High efficiency video coding (HEVC) text specification draft 10”, 12th Meeting Geneva January 2013. [Online]. Available: http://phenix.it-sudparis.eu/jct/doc_end_user/current_document.php?id=7243

[30] Yu-Wen Huang et al, “Architecture design for deblocking filter in H.264/JVT/AVC”, 2003 International Conference on Multimedia and Expo, 2003. ICME '03. Proceedings. Pages I - 693-6, vol.1, July 2003.

[31] K.R. Rao, D.N. Kim and J.J. Huang, ” Video coding standards”, Springer, 2014.

[32] Special issue on emerging research and standards in next generation video coding, IEEE transactions on circuits and systems for video technology (CSVT), vol. 22, pp. 1646-1909, Dec 2012.

[33] Special issue on emerging research and standards in next generation video coding, IEEE transactions on circuits and systems for video technology (CSVT), vol. 22, pp. 1646-1909, Dec 2013.

[34] IEEE Journal of Selected Topics in Signal Processing, vol. 7, pp.931-1151, Dec 2013.