Implementation and Analysis of Directional Discrete Cosine Transform in H.264 for Baseline Profile Shreyanka Subbarayappa Electrical Engineering Graduate

Implementation and Analysis of Directional Discrete Cosine

Transform in H.264 for Baseline Profile

Shreyanka Subbarayappa

Electrical Engineering Graduate Student

The University of Texas at Arlington

Advisor

Dr. K. R. Rao, EE Dept, UTA

Committee Members

Dr. W. Alan Davis, EE Dept, UTA

Dr Kambiz Alavi, EE Dept, UTA

AgendaAgendaIntroduction to the field of researchMotivation for the researchOverview of H.264Overview of DDCTImage Quality measuresH.264 JM 18.0 settingsExperimental ResultsConclusionsFuture workReferences

April 16, 2012Implementation and Analysis of Directional

Discrete Cosine Transform in H.264 2

Introduction to the field of Introduction to the field of researchresearch



IntroductionIntroduction Importance of video Need for compression

◦ High bandwidth requirements◦ Remove inherent redundancy

Need for standardization◦ Ensures interoperability



Year

Coding

Efficiency

Network

awareness

Complexity20052005

20102010

19991999

19941994

MPEG4MPEG4

H.264H.264

19921992MPEG1MPEG1

Video Conferencing

H.26H.2633

20032003

Mobile Phone

Hand PC

Mobile TV

SVCHDTV

MPEG2MPEG2

H.265/HECH.265/HEC/ NGVC/ NGVC

VC-1

NEED FOR IMAGE OR

VIDEO COMPRESION

2011-2013

Lossless or Lossy Lossless or Lossy CompressionCompression

Lossless compression

◦ There is no information loss, and the image can be reconstructed exactly the same as the original

◦ Applications: Medical imagery, Archiving

Lossy compression

◦ Information loss is tolerable.

◦ Applications: commercial distribution (DVD) and rate constrained environment where lossless methods cannot provide enough compression ratio



Motivation for the researchMotivation for the research



Motivation for implementing DDCT in Motivation for implementing DDCT in H.264H.264

Choice of codecs◦ Prevalence of H.264

Need for DDCT in H.264◦ New concept in the

transform domain◦ Better coding gain◦ Better image quality◦ Implemented in the other

upcoming standards like H.265

◦ Larger applications for H.264 in communication fields, data storage and streaming.


Discrete Cosine Transform in H.264 .7

Broadcast

Streaming

Content Server

Internet

Link

Mobile

Storage

H.264

ISO media file format

Overview of H.264Overview of H.264

April 16, 2012Implementation and Analysis of Directional Discrete Cosine Transform in H.264 8

H.264: OverviewH.264: Overview

Latest block-oriented motion-compensation-based codec.

Good video quality at substantially lower bit rates.

Better rate-distortion performance and compression efficiency than MPEG-2 [42].

Simple syntax specifications, very flexible.Network friendly.Wide variety of applications such as video

broadcasting, video streaming, video conferencing, D-Cinema, HDTV.



H.264 – Encoder [1]H.264 – Encoder [1]



H.264 – Decoder [1]H.264 – Decoder [1]

April 16, 2012Implementation and Analysis of Directional Discrete

Cosine Transform in H.264 11

Profiles in H.264 [1]Profiles in H.264 [1]



13 Implementation and Analysis of Directional Discrete

Cosine Transform in H.264April 16, 2012

Tools introduced in FRExts and their classification under the new high profiles

Overview of D-DCTOverview of D-DCT



OutlineOutline



Problem:- To replace the DCT-like transform for intra prediction residuals in AVC and the associated zigzag scan pattern-Solution: Directional Discrete Cosine Transform (DDCT)

DDCT:- The transforms- Properties

Implementation - Transform- Quantization-Scanning pattern

Complexity- Computation - Memory

Conventional DCT [3]Conventional DCT [3]



- The 2-D discrete cosine transform (DCT) of a square or a rectangular block shape is used for almost all block-based transform schemes for image and video coding.

- Implemented separately through two 1-D transforms, one along the vertical direction and another along the horizontal direction.- The conventional DCT seems to be the best choice for image blocks in which vertical and/or horizontal edges are dominating.

+

(M 1D-DCT s of Length N)



Forward 2D DCT (NXM) [3]

Inverse 2D DCT (NXM) [3]

x(n,m) = Samples in the 2D data domain.

XC2 (k, l) = Coefficients in the 2D-DCT domain

Limitations of conventional DCT

• It is not very efficient when the conventional DCT is applied to an image block in which other directional edges dominate.• When the first 1-D DCT (vertical or horizontal) is applied, the nonzero coefficients are not well aligned across different columns (or rows). Consequently, the second 1-D DCT may produce more nonzero coefficients

Modes Of DDCT [4]Modes Of DDCT [4]



Mode 0 – VerticalMode 1 – HorizontalMode 2 – DC (Ignored for DDCT modes)Mode 3 – Diagonal down leftMode 4 – Diagonal down right

Mode 5 – Vertical rightMode 6 – Horizontal downMode 7 – Vertical leftMode 8 – Horizontal up

Mode 3 DDCT- Diagonal Down LeftMode 3 DDCT- Diagonal Down Left



Step 1: (X00, X01,…… ,X32, X33)- Pixels in the 2-D spatial domain.

Step 2: 1D- DCT is performed for the 4X4block in diagonal down-left position with lengths L=1, 2, 3, 4, 3, 2, 1.

(A,B,C,……O,P)- coefficients in the DCT domain.

Step 3: The coefficients of step2 after 1D DCT are arranged vertically as shown in the figure.Apply Horizontal 1D- DCT for lengths L=7, 5, 3 and 1 and arranged in the same pattern

STEP 1 STEP 2 STEP 3

PIXELS Coefficients

Coefficients



STEP 4 STEP 5

Step 4: Apply Horizontal 1D- DCT for lengths L=7, 5, 3 and 1, the coefficients are arranged in the same pattern as shown in the figure step 4.

Step 5: After Step 4, move all 2D (4X4) Directional DCT coefficients to the left.Implement quantization followed by 2D VLC for compression/coding along zig-zag scan.This scanning helps to increase the runlength of zero (transform) coefficients leading to

reduced bit rate in the 2D-VLC coding (similar to JPEG [12]).

CoefficientsCoefficients

Mode 4 DDCT- Diagonal Down Mode 4 DDCT- Diagonal Down RightRight




Step 1: X00, X01, ….., X33 are the pixels in the 2D spatial domain.

Step 2: 1D DCT is performed for the 4X4 block in diagonal down-right position with lengths L= 1, 2, 3, 4, 3, 2 and 1.

Step 3: The coefficients of step 2 after 1 D DCT are arranged vertically in the same pattern as shown in step 3. Then apply horizontal 1 D DCT for lengths L = 7, 5, 3 and 1 and arrange in the same pattern.

CoefficientsCoefficientsPIXELS

Implementation and Analysis of Directional Discrete Cosine Transform in H.264 22

STEP 4 STEP 5

Step 4: Apply horizontal 1 D DCT for lengths L= 7, 5, 3 and 1. The coefficients are arranged the same pattern as shown in step4.

Step 5: After step 4, move all 2D (4X4) directional DCT coefficients to the left. Implement quantization followed by 2D VLC for compression/coding zigzag scan.

April 16, 2012

Coefficients

Mode 5 DDCT- Vertical RightMode 5 DDCT- Vertical Right





Step 2: 1D DCT is performed for the 4X4 block in vertical-right position with lengths L= 2,4,4,4,2.

Step 3: The coefficients of step 2 after 1 D DCT are arranged vertically in the same pattern as shown in step 3. Then apply horizontal 1 D DCT for lengths L = 5, 5, 3 and 3and arrange in the same pattern.

CoefficientsCoefficients

PIXELS



STEP 4 STEP 5

Step 4: Apply horizontal 1 D DCT for lengths L= 5, 5, 3 and 3. The coefficients are arranged the same pattern as shown in step 4.

Step 5: After step 4, move all 2D (4X4) Directional DCT coefficients to the left. Implement quantization followed by 2D VLC for compression/coding zigzag scan as shown in step 5. This scanning helps to increase the run-length of zero (transform) coefficients leading to reduce bit rate in 2D-VLC coding (similar to JPEG).

Coefficients

Mode 6 DDCT- Horizontal downMode 6 DDCT- Horizontal down





Step 2: 1D DCT is performed for the 4X4 block in Horizontal down position with lengths L= 2, 4, 4, 4 and 2.

Step 3: The coefficients of step 2 after 1 D DCT are arranged vertically in the same pattern as shown in step 3. Then apply horizontal 1 D DCT for lengths L = 5, 5, 3 and 3 and arrange in the

same pattern.

Coefficients CoefficientsPIXELS



STEP 4 STEP 5


Step 5: After step 4, move all 2D (4X4) directional DCT coefficients to the left. Implement quantization followed by 2D VLC for compression/coding zigzag scan as shown in step 5. This

scanning helps to increase the run-length of zero (transform) coefficients leading to reduce bit rate in 2D-VLC coding (similar to JPEG).

Coefficients

Mode 7 DDCT- Vertical LeftMode 7 DDCT- Vertical Left




Step 1 X00, X01, ….., X33 are the pixels in the 2D spatial domain.

Step 2: 1D DCT is performed for the 4X4 block in Vertical left position with lengths L= 2,4,4,4 and 2 as shown in step 3.

Step 3: The coefficients of step 2 after 1 D DCT are arranged vertically in the same pattern as shown in step 3. Then apply horizontal 1 D DCT for lengths L = 5, 5, 3 and 3 and arrange in the

same pattern.

Coefficients

CoefficientsPIXELS



STEP 4 STEP 5

Step 4: Apply horizontal 1 D DCT for lengths L= 5, 5, 3 and 3. The coefficients are arranged the same pattern.

Step 5: After step 4, move all 2D (4X4) Directional DCT coefficients to the left. Implement quantization followed by 2D VLC for compression/coding zigzag scan as shown in step 3.

Coefficients

Mode 8 DDCT- Horizontal UpMode 8 DDCT- Horizontal Up





Step 2: 1D DCT is performed for the 4X4 block in Horizontal Up position with lengths L= 2, 4, 4, 4 and 2 as shown step 2.

Step 3: The coefficients of step 2 after 1 D DCT are arranged vertically in the same pattern as shown in step 3. Then apply horizontal 1 D DCT for lengths L = 5, 5, 3 and 3 and arrange in the same pattern.

Coefficients CoefficientsPIXELS



STEP 4 STEP 5


Step 5: After step 4, move all 2D (4X4) directional DCT coefficients to the left. Implement quantization followed by 2D VLC for compression/coding zigzag scan as shown in step 5. This scanning helps to increase the run-length of zero (transform)

coefficients leading to reduce bit rate in 2D-VLC coding (similar to JPEG [4]).

Coefficients

Obtaining Mode 3 from Mode 4Obtaining Mode 3 from Mode 4



Rotate pixels by –pi/2 ( counterclock wise by 90°) to get Mode 4

Pixels

Pixels

Pixels

STEP BY STEP MODE CHANGESTEP BY STEP MODE CHANGE



MODE 3

-π/2=

MODE 4Pixels Pixels Coefficients

Step 1: Rotate the pixels by –π/2

Step 2: Perform 1-D DCT with Length = 1, 2, 3, 4, 3, 2, 1

Step 3: We get the coefficients of mode 3 (Diagonal Down Left) from mode 4 (Diagonal Down Right) as shown in figure 3.




Rotate pixels by reflecting across the diagonal axis to get Mode 6

Pixels

Pixels

Pixels




Rotate pixels by reflecting across the horizontal axis to get Mode 7

Pixels

Pixels

Pixels




Rotate pixels by pi/2 (clockwise by 90°) to get Mode 8

Pixels

Pixels

Pixels

Eigen or Basis ImagesEigen or Basis Images



Mapping of a 2D data array into a 2D DCT domain implies decomposing the 2D data array into the basis images of the DCT.

Computation of basis images for diagonal down left (a) The original 4X4 block with diagonal down left computation (b) The 1 D DCT of coefficients for lengths 7, 5, 3 and 1 for basis image (0, 0) (c) The 1 D DCT of coefficients for lengths 7, 5, 3 and 1 for basis image (0,1) (d) The 1 D DCT of coefficients for lengths 7, 5, 3 and 1 for basis image (3,3)

Mode 3 Diagonal Down Left Eigen Image (1,1) matrix Mode 3 Diagonal Down Left Eigen Image (1,1) matrix Computation for 4X4 blockComputation for 4X4 block

Step 1: Horizontal 1D-DCT for length =7, 5, 3, 1

Step 2: Coefficients of 1D-DCT for length =7, 5, 3, 1

Step 3: Put back the coefficients in the block form

Step 4: 1 D DCT of diagonal down left with lengths = 1, 2, 3, 4, 3, 2 and 1

Step 5: Putting back the coefficients of step 4 1 D-DCT we get (1,1) basis image for 4X4 block



MODE 3 - Diangonal down left basis images for 4X4 block of an image



MODE 3 - Diangonal down left basis images for 8X8 block of an image



MODE 0 or 1 – Vertical or Horizontal basis images for 8X8 block of an image



MODE 5 – Vertical right basis images for 8X8 block of an image

Computation of DDCT for an imageComputation of DDCT for an image



Image Quality MeasuresImage Quality Measures





•Criteria to evaluate compression quality

•Two types of quality measures Objective quality measure- PSNR, MSE Structural quality measure- SSIM [29]

• SSIM emphasizes that the human visual system is highly adapted to extract structural information from visual scenes. Therefore, structural similarity measurement should provide a good approximation to perceptual image quality.

•MSE and PSNR for a NxM pixel image are defined as

M

m

N

n

nmynmxNM

MSE1 1

2,,*

1

MSE

LPSNR

2

10log10

where x is the original image and y is the reconstructed image. M and N are the width and height of an image and ‘L’ is the maximum pixel value in the NxM pixel image.

Image Quality Measures



• The SSIM index is defined as a product of luminance (l), contrast (c) and structural (s) comparison functions.

where , α>0, β>0 and γ >0 are parameters used to adjust the relative importance of the three components

where μ is the mean intensity, and σ is the standard deviation as a round estimate of the signal contrast. C1 and C2 are constants.

H.264 JM18.0 [24] settingsH.264 JM18.0 [24] settings





4.4.2 Encoder Configuration in JM 18.0

• FramesToBeEncoded = 1 #Number of Frames to be coded• ProfileIDC = 66 # Profile IDC (66 = baseline, 77 = main, 88 = extended; FREXT Profiles: 100 = High, 110= High 10, 122= High 4:2:2, 244 = High 4:4:4, 44= CAVLC 4:4:4 Intra, 118 = Multiview High Profile,128 = Stereo High Profile)• IntraProfile = 1 # Activate Intra Profile for FRExt (0: false, 1: true) #(e.g. ProfileIDC = 110, IntraProfile = 1 => High 10 Intra Profile)• Transform8X8Mode = 0 # (0: only 4X4 transform, 1: allow using 8X8 transform additionally, 2: only 8X8 transform•Transform 16X16Mode=0 #(0: no 16X16 mode, 1: allow 16X16 mode)• Input YUV file: foreman_qcif.yuv• Output H.264 bitstream: test.264• Output YUV file: test_rec.yuv• YUV format: YUV 4:2:0• Frames to be encoded: 1• Frequency used for encoded bitstream: 30.00 fps• DistortionSSIM = 1 # Compute SSIM distortion (0: disable/default, 1: enabled)

Experimental Results and Experimental Results and GraphsGraphs



QCIF and CIFQCIF and CIF

49 Implementation and Analysis of Directional

Discrete Cosine Transform in H.264April 16, 2012

• CIF (Common Intermediate Format), is a format used to standardize the horizontal and vertical resolutions in pixels for sequences in video signals, commonly used in video teleconferencing systems.

•The CIF "image sizes" were specifically chosen to be multiples of macroblocks (i.e. 16 × 16 pixels) due to the way that discrete cosine transform based video compression/decompression is handled. So, by example, a CIF-size image (352 × 288) corresponds to 22 × 18 macroblocks

•QCIF means "Quarter CIF". To have one fourth of the area as "quarter" implies the height and width of the frame are halved. QCIF-size image is 176 x 144.



Bit Rate (kbps) QP (I frame)

PSNR in dB

MSESSIM

5590.56 0 79.159 0.00079 1

5232.48 4 68.825 0.00852 1

3891.84 8 57.204 0.12378 0.9995

2168.16 16 48.86 0.84553 0.9965

1088.88 24 41.803 4.29364 0.9846

745.68 28 38.892 8.39157 0.9735

331.92 36 33.173 31.32035 0.9342

152.64 44 27.981 103.5018 0.8388

72 51 23.335 301.693 0.6703

Image metrics for Foreman QCIF sequence in integer DCT implementation in H.264



Bit Rate(kbps)PSNR in

dBMSE SSIM

5486.9690.357 0.00006 1

5201.9682.436 0.00068 1

3882.5369.689 0.0014 1

2264.6360.147 0.00842 0.9996

1153.8452.976 0.55385 0.9972

686.5441.876 2.43788 0.9925

302.5338.653 10.2537 0.9801

142.5334.642 50.4376 0.9208

6730.764 110.268 0.8674

Image metrics for Foreman QCIF sequence in DDCT implementation in H.264



QP (I frame) Encoding Time of Int-DCT (sec)Encoding Time of DDCT (sec)

0 10.87618.96

4 10.03218.096

8 9.18317.264

16 7.29215.367

24 5.66612.5437

28 4.96811.0642

36 4.06710.853

44 3.4849.638

51 3.0738.428

Encoding Time of I frame for Foreman QCIF sequence in DDCT and Int-DCT implementation in H.264



PSNR v/s bit rate for DDCT and integer DCT for foreman QCIF sequence



MSE v/s bit rate for DDCT and integer DCT for foreman QCIF sequence



SSIM v/s bit rate for DDCT and integer DCT for foreman QCIF sequence



Encoding time v/s quantization parameter for DDCT and integer DCT for Foreman QCIF sequence

Test sequence used for simulationTest sequence used for simulation



Bit Rate:72kbits/frame Bit Rate:67kbits /frame

Properties of DDCTProperties of DDCT



• Adaptivity: Unlike AVC in which the same DCT-like transform is applied to the intra prediction errors for all intra prediction modes of the same block size (4x4, 8x8, or 16x16), DDCT assigns a different transform and scanning pattern to each intra prediction mode. These transforms and scanning patterns are designed taking into account the intra prediction direction.

• Directionality: Since the intra prediction mode is known, the DDCT is designed with the knowledge of the intra prediction direction. By first applying the transform along the prediction direction, DDCT has the potential to minimize the artifacts around the object boundaries.

• Symmetry: Although there are 22 DDCTs for 22 intra prediction modes (9 modes for 4x4, 9 modes for 8x8, and 4 modes for 16x16), these transforms can be derived, using simple operators such as rotation and/ or reflection, from only 7 different core modes.

ConclusionsConclusions





Directional DCT has a better coding gain when compared to integer DCT

• PSNR value for DDCT is more when compared to Integer DCT.

• MSE value of DDCT is less compared to integer DCT for the same bit rates.

• SSIM graph shows that the value obtained for different bit rates is almost 1 for DDCT when compared to Integer DCT.

• Foreman frame of QCIF format gives a better quality image obtained from DDCT with respect to the output obtained from Integer DCT.

Drawback of DDCT

• Encoding time for DDCT is more when compared to integer DCT.

Future WorkFuture Work



Future workFuture work



• DDCT can be extended to other video standards that use integer DCT in the transform domain.

• It can be extended for the entire video – inter frame prediction.

•It can be extended to other profiles in H.264 like main and extended profiles.

•Only 8 modes are described in this research. These can be extended to other directional modes. Payoff between increasing complexity and improved visual quality can be investigated.

ReferencesReferences





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Implementation and Analysis of Directional Discrete Cosine Transform in H.264 for Baseline Profile Shreyanka Subbarayappa Electrical Engineering Graduate