Topics in Signal Processing

Download 118.25 Kb.

Date	20.10.2016
Size	118.25 Kb.
	#6416

Topics in Signal Processing

Course ID: EE5359

Final Report: HEVC Lossless Coding and Improvements

SUBMITTED BY: SUJATHA GOPALAKRISHNAN

STUDENT ID: 1001024145

ACRONYMS 2

HEVC 4

Block Diagram HEVC 5

HEVC Lossless Coding 6

Block Diagram HEVC Lossless Coding 6

Basic Definitions 7

H.264 [1] [2] 7

Inter Frame 7

Intra Frame 7

Loop Filters 7

De-blocking Filter 8

Sample Adaptive Offset 8

Block-Based Angular Intra Prediction 8

Sample-Based Angular Intra Prediction 8

Coding Tools 8

LCU/CTU 8

Parallel Processing 9

Entropy Coding 9

Motion Estimation 9

Motion Compensation 10

DCT for HEVC lossless compression 10

Improved HEVC lossless compression using Two-Stage coding 11

Algorithm of Sample Based Angular Intra Prediction 12

Pixel-based averaging predictor 13

NLM Algorithm 14

Low-Complexity Pixel wise Predictor Implementation 17

Test Sequences 18

Test Sequence 1 18

Test Sequence 2 19

Test Sequence 3 21

Test Sequence 4 22

Project Results 23

Conclusions 23

Future Work 24

References 24

ACRONYMS

2D	Two dimension
3D	Three dimension
ACM MoVid	Association for Computer Machinery Mobile Video
AHG	Ad Hoc Groups
AIF	Adaptive Interpolation Filter
ALF	Adaptive Loop Filter
AMVP	Advanced Motion Vector Prediction
APIF	Adaptive Pre-Interpolation Filter
ASIC	Application-Specific Integrated Circuit
AVC	Advanced Video Coding
AVS	Audio Video Standard
BBC	British Broadcasting Corporation
BD	Bjontegaard Distortion
BL	Base Layer
bpp	Bits per pixel
BS	Boundary Strength
CU	Coding Unit
CI	Confidence Interval
CABAC	Context Adaptive Binary Arithmetic Coding
CPU	Central Processing Unit
CRA	Clean Random Access
CSVT	Circuits and Systems for Video Technology
CU	Coding Unit
DCT	Discrete Cosine Transform
DCTIF	Discrete Cosine Transform Interpolation Filters
DDCT	Directional Discrete Cosine Transform
DSP	Digital Signal Processing
DST EURASHIP	Digital Sine Transform European Signal Processing
EC	Error Concealment
FIR	Finite Impulse Response
FPGA	Field Programmable Gate Array
fps	Frames per second
GPU	Graphics Processing Unit
HDR	High Definition Range
HEVC	High efficiency video coding
HEVStream	High Efficiency Video Stream
HTTP	Hyper Text Transfer Protocol
ICIEA	IEEE Conference on Industrial Electronics and Applications
IEEE	Institute of Electrical and Electronics Engineers
INTDCT	Integer Discrete Cosine Transform
intra HE	Intra high efficiency
IPTV	Internet Protocol Television
IS & T	Information Systems and Technology
ISO	International Organization for Standardization
ITU-T	Telecommunication Standardization Sector of the International Telecommunications Union
IVMSP	Image, Video, and Multidimensional Signal Processing
JCTVC	Joint Collaborative Team on Video Coding
JM	Joint Model
JPEG	Joint Photographic Experts Group
JPEG-XR	JPEG extended range
JSVM	Joint Scalable Video Model
JTC	Joint Technical Committee
LR	Low Resolution
Mbit/s	Megabit per second
MC	Motion Compensation
MDDCT	Modified Directional Discrete Cosine Transform
MDDT	Mode-Dependent Directional Transform
ME	Motion Estimation
MJPEG	Motion JPEG
MMSP	Multimedia Signal Processing
MPEG	Moving Picture Experts Group
Mpixel	Megapixel
Mpm	Most Probable Modes
MV	Motion Vector
NAB	National Association of Broadcasters
NAL NLM	Network Abstraction Layer Non-Local Means
PCM	Pulse Code Modulation
PSNR	Peak-to-peak signal to noise ratio
PU	Prediction Unit
QP	Quantizer parameter
RD	Rate Distortion
RDOQ	Rate-distortion optimized quantization
RDPCM	Residual Differential Pulse Code Modulation
ROT	Rotational Transform
RTP	Real-time Transport Protocol
SAO SAP	Sample adaptive offset Sample based Angular Intra-Prediction
SHVC	Scalable High Efficiency Video Coding
SVC	Scalable Video Coding
SELC	Sample based weighted prediction for Enhancement Layer Coding
SIP	Signal and Image Processing
SSVC	Spatially Scalable Video Coding
TB	Transform Block
TU	Transform Unit

HEVC

High Efficiency Video Coding (HEVC) [1] [2] is a video compression standard, a successor to H.264/MPEG-4 AVC [22]. HEVC is said to double the data compression ratio compared to H.264/MPEG-4 AVC [1] at the same level of video quality [2].
The design of most video coding standards is primarily aimed at having the highest coding efficiency
HEVC benefits from the use of larger Coding Tree Unit (CTU) sizes.
The HEVC video coding layer uses the same "hybrid" approach used in all modern video standards, starting from H.261 [1], in that it uses inter-/intra-picture prediction and 2D transform coding.
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 [10] [11]. Figure 1 shows the block diagram of HEVC encoder [2].

Block Diagram HEVC

Figure : HEVC Encoder [2]

Figure : HEVC Decoder Block Diagram [3]

Some differences in HEVC [1][2] are coding tree units instead of macro blocks, single entropy coding methods-Context Adaptive Binary Arithmetic Coding (CABAC) [15] method and features like tiles , wave front parallel processing and dependent slices to enhance parallel processing. Figure 2 shows the block diagram of HEVC decoder [3].

HEVC Lossless Coding

The lossless coding mode of HEVC main profile bypasses transform quantization and in-loop filters as shown in the fig.2 [4][19].
Comparing it with non-lossless coding mode, it has smallest quantization parameter value.
Lossless coding mode provides perfect fidelity and average bit rate reduction.
Outperforms the existing lossless compression standars such as JPEG-2000 [22] and JPEG-LS [22].
It can prevent accumulation of quantization errors in repeated encoding and decoding operations of video editing
In this method it is essential to preserve numerical video data with fewer bits.
DCT coefficients i.e., float-point numbers have to be quantized instead of DCT.
Lossless video coding is used when perfect preservation of video data is required [29].
It employs Sample Angular-based Intra-Prediction (SAP) [4].

Same prediction mode signaling method.
Same interpolation method of HEVC.
Uses adjacent neighbors as reference shown in fig.8.
Prediction residuals are coded with the entropy coder in the spatial domain [29].

Block Diagram HEVC Lossless Coding

Figure : HEVC lossless Algorithm Block Diagram [4]

Figure 3 shows the block diagram of HEVC lossless algorithm [4]. The blocks that are marked bypass are not being used when implementing a HEVC [1] [2] lossless algorithm, thereby providing average bit rate reduction.

Basic Definitions

H.264 [1] [2]

H.264/MPEG-4 AVC [1] [2] [22] is a block-oriented, motion-compensation based video compression standard.

Inter Frame

An inter frame is a frame in a video compression stream which is expressed in terms of one or more neighboring frames. The "inter" part of the term refers to the use of Inter frame prediction.

Intra Frame

The term intra-frame refers to the various lossless and lossy compression techniques that happens relative to information which is contained only within the current frame and not relative to any other frame in the video sequence.

Loop Filters

HEVC [1] specifies two loop filters that are applied sequentially; the de-blocking filter (DBF) [4] applied first and the sample adaptive offset (SAO) filter applied afterwards. Both loop filters are applied in the inter-picture prediction loop, i.e. the filtered image is stored in the decoded picture buffer (DPB) as a reference for inter-picture prediction.

De-blocking Filter

The DBF is similar to the one used by H.264/MPEG-4 AVC [1] [2], but with a simpler design and better support for parallel processing.
DBF first apply horizontal filtering for vertical edges to the picture and only after that does, it apply vertical filtering for horizontal edges to the picture. This allows for multiple parallel threads to be used for the DBF [1].

Sample Adaptive Offset

The SAO filter is applied after the DBF and is designed to allow for better reconstruction of the original signal amplitudes by applying offsets stored in a lookup table in the bit stream.

Block-Based Angular Intra Prediction

It is a method of computing predicted samples produced by PU when lossless coding is not enabled. It is defined to exploit spatial sample redundancy in intra coded CUs. As shown in the fig.4, a total of 33 angles are defined for the angular prediction, which can be categorized into two classes: vertical and horizontal angular predictions as illustrated [14].

Figure : Block Based Angular Intra Prediction in HEVC [4]

Sample-Based Angular Intra Prediction

It is a method of computing predicted samples produced by PU when lossless coding is enabled. It is explained detail in the following.

Coding Tools

Coding efficiency is the ability to encode video at the lowest possible bit rate while maintaining a certain level of video quality. This could be achieved with the following coding tools.

LCU/CTU

Coding tree unit (CTU) as shown in figure 5 is the basic processing unit of the HEVC video standard and conceptually corresponds in structure to macroblock units, which were used in several previous video standards. CTU is also referred to as largest coding unit (LCU) [1] [2]. In the HEVC, one frame is divided into a series of non-overlapped Coding Tree Unit (CTU) [9] [12].

Figure : Division of a CTB into CBs and transform blocks TB [2]

Parallel Processing

A picture is divided into tiles. Main purpose of these tiles is that, they can be decoded /encoded individually in a simultaneous way called parallel processing. Parallel computing is basically a technique in which multiple computation tasks are assigned to multiple processes and process the job simultaneously. The basic approach for parallel processing is to break the task into multiple smaller tasks and further assign each task to each of the thread which performs required operations in parallel. Parallelization can sometimes get complicated due to race conditions, data dependency, synchronization and communication among different threads [13].

Entropy Coding

HEVC uses a context-adaptive binary arithmetic coding (CABAC) algorithm that is fundamentally similar to CABAC in H.264/MPEG-4 AVC. CABAC is the only entropy encoder method that is allowed in HEVC while there are two entropy encoder methods allowed by H.264/MPEG-4 AVC. CABAC and the entropy coding of transform coefficients in HEVC are designed for a higher throughput than H.264 while maintaining higher compression efficiency for larger transform block sizes relative to simple extensions [15][16]. These techniques include reducing context coded bins, grouping bypass bins, grouping bins with the same context, reducing context selection dependencies, reducing total bins, and reducing parsing dependencies. It also describes reductions to memory requirements that benefit both throughput and implementation costs.

Motion Estimation

Motion estimation [5] is an essential process in many video coding standards like MPEG-2, H.264/AVC and HEVC [1] [2]. Motion estimation has been used at the encoder. Motion Estimation itself consumes more than 50% coding complexity or time to encode. To reduce the computation time, many fast motion estimation Algorithms were proposed and implemented [5]. HEVC allows for two MV modes which are Advanced Motion Vector Prediction (AMVP) and merge mode. AMVP uses data from the reference picture and can also use data from adjacent prediction blocks. The merge mode allows for the MVs to be inherited from neighboring prediction blocks. Merge mode in HEVC is similar to "skipped" and "direct" motion inference modes in H.264.

Motion estimation process (as represented in figure 6) in HEVC consumes more than 50% coding complexity or time to encode with equal perceptual quality [6] [7]. Many block based motion estimation algorithms [8] [9] are proposed and also implemented to reduce the computation time.

Figure : Illustration of Motion Estimation process [5]

Motion Compensation

The interpolation of fractional luma sample positions HEVC uses separable application of one-dimensional half-sample interpolation, with an 8-tap filter or quarter-sample interpolation with a 7-tap filter [5]. While H.264/MPEG-4 AVC[1][2] uses a two-stage process that first derives values at half-sample positions, using separable one-dimensional 6-tap interpolation followed by integer rounding; then applies linear interpolation between values at nearby half-sample positions to generate values at quarter-sample positions. HEVC has improved precision due to the longer interpolation filter and the elimination of the intermediate rounding error. As in H.264/MPEG-4

AVC [1] [2], a scaling and offset operation may be applied to the prediction signal(s) in a manner

Known as weighted prediction [1].

DCT for HEVC lossless compression

DCT is applied to prediction residuals.
DCT coefficients are quantized.
Quantized DCT coefficients and quantization error are coded.
Coding of each unit is performed by adaptive quantization parameters.

Improved HEVC lossless compression using Two-Stage coding

Block of residual signal is separated into two parts:

Part 1: Quantized DCT coefficients.
Part 2: Quantization error.

Quantized coefficients are used to reconstruct a lossy decoded block which is subtracted from the residual block.
Quantization error is encoded as the spatial block as shown in figure 7. Table 1 [30] represents coded block for two-stage coding. Table 2 [30] represents the performance of two-stage coding.

Figure : Two stage lossless coding [30]

table 1

Table : Coded block flag for two-stage coding [30].

Setting	Average Coding gain of Two stage coding
720 Intra	12.14%
720 Intra+Inter	5.69%
480 Intra	4.48%
480 Intra+Inter	1.64%

Table : Performance of two-stage coding [30].

Algorithm of Sample Based Angular Intra Prediction

The SAP [4] is designed to better exploit the spatial redundancy in the lossless coding mode by generating intra prediction samples from adjacent neighbors. The design principle here is very similar to the sample-based DPCM in [21] [4] H.264/MPEG-4 AVC [20] [4] lossless coding, but SAP [4] is fully harmonized with the HEVC block-based angular intra prediction, and can be applied to all the angular intra prediction modes specified in HEVC [4].

As shown in the fig.8 SAP is performed sample by sample. The adjacent neighboring samples

of the current sample

in the current PU are used for prediction. That is, the reference samples used for prediction are not limited to those boundary reference samples from the left and upper neighboring PUs. The SAP has to be processed in a predefined order to ensure the availability of these adjacent neighbors for prediction.

Figure : Algorithm of SAP [4]

Pixel-based averaging predictor

Lossless video compression of noisy video content can be improved if the noise within the video is considering the compression [32].
In HEVC lossless coding block-wise processing is not needed, pixel-wise prediction could be performed for better spatial correlation within the image or a video signal [31].
De-noised intra prediction scheme is used, where de-noising is performed by the predictor instead of removing the noise.
Non-local means (NLM) algorithm as shown in figure 9 [32] is used for de-noising [33].

Figure : NLM algorithm for image de-noising [32].

Pixel-wise prediction is the combination of linear predictors with exponentially decaying weights from NLM algorithm.
Developed predictor results in a weighted average of surrounding pixels.
Other non-local predictors e.g., forward adaptive scheme where intra-frame motion compensation is performed [34] [32] or a backward adaptive scheme where template matching is performed for prediction [35] [36] [32], are designed for block-wise lossy prediction in H.264/AVC and thus are not efficient for lossless compression.

NLM Algorithm

The Non-Local Means (NLM) [31] algorithm has been introduced in [32] for image de-noising. In NLM de-noising, the estimate for a de-noised version of a noisy pixel is established by averaging all the pixels in the local as well as non-local neighborhood. The process of NLM [31] de-noising is illustrated in Fig 9. In the illustrated ex-ample, the pixel g[i] should be de-noised, where i=(x,y) is the two-dimensional coordinate. Therefore all pixels in the support area S are averaged depending on their similarity to g[i].

The similarity between the pixels is measured by a certain mean distance of the pixels in the surrounding area, which is illustrated with the square around the pixels g[j1], g[j2] and g[j3]. For example the pixel g[j3] will get a higher weight than the pixels g[j1] and g[j2] because the pixels around g[j3] are more similar to the surrounding pixels of g[i]. The formal description of the originally proposed NLM algorithm is given in the following. The averaging process is described by

Ρ_NLM[i] = ∑_j_∊_sw[I,j], g[j] [31]

In order to adapt the NLM algorithm for prediction purposes, some modifications have to be made which follow the causal relations in video encoding. We construct a weighted average of the causal pixels (i.e., S contains only the coordinates of causally available pixels) for prediction of pixel X.

To measure the similarity of the candidate pixels to the pixel which is to be predicted, we perform a distance calculation. However, only the causal pixels around X without X itself can be used for the patch describing the neighborhood of X for the similarity measure i.e., N_o contains only the shifts to coordinates of causally available pixels.
For example different sized patches as illustrated in Fig 10. can be used. The same patches have to be used for the possible candidates in the neighborhood for distance calculation. For possible neighborhoods from where the prediction is performed, we could use the same shapes as are used for patches. For example Neighbor-hood 6 would mean that uses the same shape as is illustrated for Patch6 in Fig 10.
An example of a possible constellation for the NLM predictor is given in Fig 11. In this example, Patch2 and Neighborhood6 are used in the prediction process. It means that the pixels a … z are used for weighted average prediction of the pixel X.

Figure : Casual patches for NLM predictor [31]

Figure : Patch 2 and neighborhood 6 [31]

Low-Complexity Pixel wise Predictor Implementation

Run time for prediction is proportional to the neighborhood size or the patch size.
If the patch becomes larger, structural complexity of the patch becomes higher, so it becomes harder to find similar patches.
Hence patch and neighborhood sizes are reduced in NLM predictor.
Results of the investigated parameter constellations are shown in Table 3 [32].

Table : Compression results of the proposed pixel-wise prediction [32].

Test Sequences

Sequences are obtained from [29] and experimented to obtain the performance based on various parameters described as follows.

Test Sequence 1

Figure : Race horse sequence [29]

Test Sequence	Resolution	Frame rate (fps)
RaceHorses_416x240_30.yuv	416 x 240	30

Test sequence		Intra Profile	Random Access Profile	BD- % Bit rate reduction	BD- PSNR(dB)
Race horse sequence	PSNR (dB)	34.2442	33.7342	-22.4269	1.483
	Bitrate(kbps)	1842.6421	371.49
	Encoding time(sec)	24.332	119.764
	Decoding time(sec)	0.840	4.134

Test Sequence 2

Figure : Basketball drill sequence [29]

Test Sequence	Resolution	Frame rate (fps)
BasketballDrill_832x480_50.yuv	832 x 480	50

Test sequence		Intra Profile	Random Access Profile	BD- % Bit rate reduction	BD- PSNR(dB)
Basketball drill	PSNR (dB)	37.2947	35.7193	-32.8763	1.956
	Bitrate(kbps)	5941.7732	817.87
	Encoding time(sec)	97.539	347.891
	Decoding time(sec)	1.2	4.28

Test Sequence 3

Figure 14: Kristen and Sara sequence [29]

Test Sequence	Resolution	Frame rate (fps)
KristenandSara_1280x720_60.yuv	1280 x 720	60

Test sequence		Intra Profile	Random Access Profile	BD- % Bit rate reduction	BD- PSNR(dB)
Kristen and Sara	PSNR (dB)	41.8887	41.6543	-33.541	2.783
	Bitrate(kbps)	10454.1962	947.28
	Encoding time(sec)	203.148	615.423
	Decoding time(sec)	2.5	6.31

Test Sequence 4

Figure 15: Park Scene sequence [29]

Test Sequence	Resolution	Frame rate (fps)
ParkScene_1920x1080_24.yuv	1920 x 1080	24

Test sequence		Intra Profile	Random Access Profile	BD- % Bit rate reduction	BD- PSNR(dB)
Park Scene	PSNR (dB)	38.2361	37.2705	-34.875	3.842
	Bitrate(kbps)	20114.4142	2685.25
	Encoding time(sec)	505.078	1745.91
	Decoding time(sec)	3.8	9.103

Project Results

BD-PSNR (dB) for the test sequences 1&2

BD-% Bit rate reduction for test sequences 1&2

Test sequence 1 [29]: Encoding and decoding times (secs) for Intra and Random access profiles

Test sequence 2 [29]: Encoding and decoding times (secs) for Intra and Random access profiles

BD-PSNR (dB) for the test sequences 3&4

BD-% Bit rate reduction for test sequences 3&4

Test sequence 3 [29]: Encoding and decoding times (secs) for Intra and Random access profiles

Test sequence 4 [29]: Encoding and decoding times (secs) for Intra and Random access profiles

Conclusions

The HM 16.0 [16] software has been used for simulation of various test sequences [29]. Results have been plotted and compared with other test sequences of various resolutions. BD- PSNR and BD Bit rate [4] have been computed and plotted. To ensure fair compression against other coding schemes, class sequences are used across the configurations. Theoretical analysis, to obtain HEVC lossless coding; through various methods were studied.

Future Work

Future simulations can be conducted using the HM 16.0 [16] software for other test sequences [29]
JPEG-LS, JPEG-2K and ZIP (archival tools) [4] can be taken into consideration for obtaining a performance comparison; based on compression ratio, BD-bitrate, BD-PSNR and computational complexity.

References

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

[2] G.J. Sullivan et al, “Standardized Extensions of High Efficiency Video Coding (HEVC)”, IEEE Journal of selected topics in Signal Processing, vol.7, pp.1001-1016, Dec. 2013.

[3] C. Fogg, “Suggested figures for the HEVC specification”, ITU-T/ISO/IEC Joint Collaborative Team on Video Coding (JCT-VC) document JCTVC- J0292r1, July. 2012.

[4] M. Zhou et al, “HEVC lossless coding and improvements”, IEEE Trans, CSVT, vol.22, pp.1839-1843, Dec. 2013.

[5] N. Purnachand et al, "Fast Motion Estimation Algorithm for HEVC", IEEE Second International Conference on Consumer Electronics-Berlin (ICCE-Berlin), vol.11, pp.34-37, Sep. 2012.

[6] P. Hanhart et al, “ Subjective quality evaluation of the upcoming HEVC video compression standard”, SPIE Optical Engineering+ Applications, International Society for Optics and Photonics, vol. 8499, pp.84990v-84990v, Aug. 2012.

[7] M. Horowitz et al, “Informal subjective quality comparison of video compression performance of the HEVC and H.264/MPEG - 4 AVC standards for low delay applications”, SPIE Optical Engineering+ Applications, International Society for Optics and Photonics, vol.84990, pp.84990w-84990w, Aug. 2012.

[8] A. Abdelazim, W. Masri and B. Noaman., "Motion estimation optimization tools for the emerging high efficiency video coding (HEVC)", IS&T/SPIE Electronic Imaging, International Society for Optics and Photonics, vol. 9029, pp. 902905-902905, Feb. 2014.

[9] M. Jakubowski and G. Pastuszak, “Block-based motion estimation algorithms-a survey”, Journal of Opto-Electronics Review, vol. 21, pp.86-102, Mar. 2013.

[10] B. Bross et al, “High Efficiency Video Coding (HEVC) Text Specification Draft 10”, Document JCTVC-L1003, ITU-T/ISO/IEC Joint Collaborative Team on Video Coding (JCT-VC), Jan. 2013, available on

http://phenix.it-sudparis.eu/jct/doc_end_user/current_document.php?id=7243

[11] J. Ascenso et al, "Improving Frame Interpolation with Spatial Motion Smoothing for Pixel Domain Distributed Video Coding", 5th EURASIP Conference on Speech and Image Processing, Multimedia Communications and Services, pp.1-6, Smolenice, Slovak Republic, July. 2005.

[12] X. Wang et al, “Paralleling Variable Block Size Motion Estimation of HEVC on Multicore CPU plus GPU platform”, IEEE International Conference on Image Processing (ICIP), vol.22, pp. 1836-1839, Sep. 2013.

[13] Introduction to parallel computing https://computing.llnl.gov/tutorials/parallel_comp/#Whatis

[14] L. Zhao et al, “Group-Based Fast mode decision algorithm for intra prediction in HEVC”, IEEE Eighth international Conference on Signal Image Technology and Internet based Systems. Article no.6115979, pp. 225-229, Nov 2011.

[15] V. Sze and M. Budagavi, "High Throughput CABAC Entropy Coding in HEVC", IEEE Transactions on Circuits and Systems for Video Technology, vol.22, no.12, pp.1778-1791, Dec. 2012.

[16] T.Nguyen et al, "Transform Coding Techniques in HEVC", IEEE Journal of Selected Topics in Signal Processing, vol.7, pp.978–989, Dec. 2013.

[17] HEVC tutorial by I.E.G. Richardson: http://www.vcodex.com/h265.html

[18] HEVC Reference Software HM16.0. https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/tags/HM-16.0rc1/

[19] B. Bross et al,“High Efficiency Video Coding (HEVC)Text Specification Draft 8”, JCT-VC document, JCTVC-J1003, Stockholm, Sweden, Jul. 2012.

http://phenix.it-sudparis.eu/jct/doc_end_user/current_document.php?id=6465
[20] Joint Video Team, “Advanced Video Coding for Generic Audiovisual Services”, ITU-T Rec. H.264 and ISO/IEC, 14496-10 (MPEG-4) AVC, pp.H.100-H.869, Feb. 2014.
[21] Y.L. Lee et al, "Improved lossless intra coding for H.264/MPEG-4 AVC", IEEE Trans on Image Process, vol.15, no.9, pp.2610-2615, Sep. 2006.

[22]K.R. Rao, D.N. Kim and J.J Hwang, “High Efficiency Video Coding (HEVC) Revised/Updated Chapter from the book Video Coding Standards”–Springer 2014.

[23] ITU-T website: http://www.itu.int/ITU-T/index.html

[24] JCT-VC documents are publicly available at http://ftp3.itu.ch/av-arch/jctvc-site and http://phenix.it-sudparis.eu/jct/

[25] V.Sze, M.Budagavi, and G.J. Sullivan “High Efficiency Video Coding (HEVC) Algorithms and architectures” Springer, 2014.

[26] Software reference manual for HM:

https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/branches/HM-9.2-dev/doc/software-manual.pdf

[27] M. Wien, “High efficiency video coding: Tools and specification”, Springer, 2015.
[28] I.E. Richardson, “Coding video: A practical guide to HEVC and beyond”, Wiley, 11 May. 2015
[29] Video Sequences:

http://forum.doom9.org/archive/index.php/t-135034.html

http://ultravideo.cs.tut.fi/

[30] C. Xun and Q. Gu, "Improved HEVC lossless compression using Two-Stage coding with Sub-Frame level optimal quantization values", IEEE International Conference on Image Processing (ICIP), vol.23, pp. 5651-5655, Oct. 2014.

[31] W. Eugen et al, "Pixel-based averaging predictor for HEVC lossless coding", IEEE International Conference on Image Processing (ICIP), vol.22, pp. 1806-1810, Sept. 2013.
[32] E. Wige et al, "In-loop denoising of reference frames for lossless coding of noisy image sequences" IEEE International Conference on Image Processing (ICIP), vol.19, pp. 461-464, Sept. 2010.
[33] A. Buades, B. Coll, and J.M. Morel, "A non-local algorithm for image denoising", IEEE Computer Society Conference, Computer Vision and Pattern Recognition (CVPR), vol.2, pp. 60-65, June. 2005.
[34] S.L. Yu and C. Chrysafis,” New intra prediction using intra-macroblock motion compensation”, Joint Video Team (JVT) of ISO/IEC MPEG &ITU-T VCEG (ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Std., doc. JVT-C151, Virginia, USA, Apr.2004.
[35] T.K. Tan, C. S. Boon, and Y. Suzuki, " Intra prediction by template matching ", IEEE International Conference on Image Processing (ICIP), vol.15, pp. 1693-1696, Oct. 2006.
[36] T.K. Tan et al, "Intra Prediction by Averaged Template Matching Predictors", IEEE Consumer Communications and Networking Conference (CCNC), vol.16, pp. 405-409, Jan 2007.
[37] V. Sze and M. Budagavi, “Design and Implementation of Next Generation Video Coding Systems (H.265/HEVC Tutorial),” IEEE International Symposium on Circuits and Systems (ISCAS), presented on June. 2014.

http://www.rle.mit.edu/eems/publications/tutorials/

Directory: faculty -> krrao -> dip -> Courses -> EE5359
faculty -> Samples of Elements Exam Question III contains All Prior Exam Qs III except
faculty -> 【Education&Working Experience】
faculty -> References Abe, M., A. Kitoh and T. Yasunari, 2003: An evolution of the Asian summer monsoon associated with mountain uplift —Simulation with the mri atmosphere-ocean coupled gcm. J. Meteor. Soc. Japan, 81
faculty -> Ralph R. Ferraro Chief, Satellite Climate Studies Branch, noaa/nesdis
faculty -> Unit IV text: Types of Oil, Types of Prices Grammar: that/those of, with revision
EE5359 -> The university of texas at arlington
EE5359 -> Scalable video coding extension of hevc (s-hevc)
EE5359 -> -
EE5359 -> “A performance comparison of fractional-pel interpolation filters in hevc and H. 264/avc”
EE5359 -> Project proposal topic: Advanced Video Coding