/
Directional DCT Directional DCT

Directional DCT - PowerPoint Presentation

ellena-manuel
ellena-manuel . @ellena-manuel
Follow
507 views
Uploaded On 2016-03-22

Directional DCT - PPT Presentation

Presented by Shreyanka Subbarayappa Sadaf Ahamed Tejas Sathe Priyadarshini Anjanappa K R RAO 1 Conventional Framework for Image Coding 9 The 2D discrete cosine transform DCT of a square or a rectangular block shape is used for almost all ID: 265830

image dct block directional dct image directional block coefficients diagonal idct basis coding direction vertical left horizontal horizontally step

Share:

Link:

Embed:

Download Presentation from below link

Download Presentation The PPT/PDF document "Directional DCT" is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.


Presentation Transcript

Slide1

Directional DCT

Presented by,-Shreyanka Subbarayappa, Sadaf Ahamed, Tejas Sathe, Priyadarshini Anjanappa

K. R. RAO

1Slide2

Conventional Framework for Image Coding [9]

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.

The NXM 2D-DCT is defined as

2

Forward

2

D DCT

x(

n,m

)= Samples in the 2D

data domain.X (k,l)= Coefficients in the 2D- DCT domain.Slide3

3

INVERSE 2D-DCTThe conventional 2D DCT: Implemented separately through two 1-D transforms, one along the vertical direction and another along the horizontal direction.

These two processes can be interchanged

T

he conventional DCT seems to be the best choice for image blocks in which vertical and/or horizontal edges are dominating.

A popular scenario in many image signals- I

mage blocks containing directional edges

+

(M 1D-DCT s of Length N)Slide4

New Framework for Image Coding [2]

Directional DCT [2] [3]: A new block based DCT framework in which the first transform may choose to follow a direction other than the vertical or horizontal one.

Coefficients produced by all directional transforms in the first step are arranged appropriately; the second transform can be applied to the coefficients that are best aligned with each other.

Compared with the conventional DCT, the resulting directional DCT framework is able to provide a better coding performance for image blocks that contain directional edges

.

Choose the best “directional” DCT according to the dominating edge(s) within each individual image block.

Mode3: Diagonal Down Left

Mode4: Diagonal Down Right

4Slide5

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.

5Slide6

Fig1: Six directional modes for the block size 8x8 (The vertical and horizontal modes are not included here)The different directional modes [5]

2 D (8X8) D-DCT

6Slide7

D-DCT Image Coding

7Slide8

Mode3 D-DCT (4X4) Block [8]

STEP 1:

(

X00, X01,…… ,X32, X33

)- Pixels in the 2-D spatial domain.

1

D- DCT is performed for the 4X4

block 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.

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 2:8

STEP

1

:

STEP

2:

STEP

3

:

STEP

3

:Slide9

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 figureSTEP

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]).

9Slide10

Basis Images For Mode3

4X4 Block DCTs of lengths 1, 2, 3, 4, 3, 2, 1.DCT of length 1 means same as the original pixel

STEP 1:

When all pixels are zero of any length, then

the corresponding length DCT yields only zeros

STEP

2

:

Repeat the procedure till you get this

10Slide11

NxN

image block in which the first 1D DCT will be performed along the diagonal down-left direction.Directional DCT for Mode 3 [5]

Fig2: The first 1D DCT:

11Slide12

Fig3: The second 1D DCT:

The coefficients after the D-DCT(mode3) are arranged in this manner vertically. 1D DCT horizontally with lengths L=15, 13, 11, 9,7,5,3 and 1

TO GET BACK THE ORIGINAL IMAGE ( INVERSE DIRECTIONAL DCT ) :

1D IDCT horizontally with lengths L=15, 13, 11,9,7,5,3,1.

Put back the coefficients in the Fig2 for 8X8 block.

1D

IDCT directionally as shown in Fig2 and put back the coefficients in the same order. The output image is same as the original image.

12

Horizontal DCTs of Length

15 13 11 9 7

5

3

1

Slide13

DIRECTIONAL DCT MODE3 OUTPUT [

5]For LENA IMAGE : mse = 1.0245e-027, PSNR = 318.0255dB

Note that no quantization and coding steps are involved. The errors are due to roundoff

/truncation in implementing the forward and inverse 2D directional DCTs.

13

8X8 Block (Diagonal Down Left)Slide14

BASIS IMAGES FOR MODE3 [5]

Keep the 1st coefficient as 1 and the remaining as zeros. Compute IDCT horizontally.Put back the coefficient in the Fig5.Compute 1D IDCT along the diagonal down-left direction and put back the coefficients in the same order back into the block.

The resulting block is 1 basis imageRepeat the same steps with the second coefficient as 1 and the remaining zero and computing IDCT horizontally and diagonal down left. The output thus obtained is 2

nd

basis image..

Repeat the same procedure for L=

15, 13, 11, 9, 7, 5, 3 and 1 to get the remaining 64 basis images

Fig4

Fig5

14Diagonal Down Left

Horizontal IDCTs of

Length

15

13

11

9

7

5

3

1

Slide15

BASIS IMAGES FOR MODE3

FOR 4X4

15

Diagonal Down LeftSlide16

FOR MODE

3 8X8 16 (Diagonal Down left)Slide17

Directional DCT for Mode 4 [5]

NxN image block in which the first 1D DCT will be performed along the diagonal down-right direction.

These coefficients are arranged vertically as shown in Fig7.

1D

DCT horizontally with lengths L

=15, 13, 11, 9,7,5,3 and 1

Fig6: 1D DCT along Diagonal down-right

Fig7: 1D DCT

horizontally

17

Horizontal DCTs of Length

15

13

11

9

7

5

3

1

Slide18

TO GET BACK THE ORIGINAL IMAGE Mode4 ( INVERSE DIRECTIONAL DCT ) :

1D IDCT horizontally with lengths L=15, 13, 11,9,7,5,3,1.Put back the coefficients in the Fig6 for 8X8 block. 1D IDCT directionally as shown in Fig6 and put back the coefficients in the same order. The output image is same as the original image.

DIRECTIONAL DCT MODE

4

OUTPUT

18

Diagonal Down RightSlide19

BASIS IMAGES FOR MODE4 [5]

Keep the 1st coefficient 1 and the remaining zero. Compute IDCT horizontally.

Put back the coefficient in the Fig9 diagonal down-right.Compute 1D IDCT along the diagonal down-right direction and put back the coefficients in the same order back into the block.

The resulting block is 1 basis image

Repeat the same steps with the second coefficient as 1 and the remaining zero and computing IDCT horizontally and diagonal down left. The output thus obtained is 2

nd

basis image.

Repeat the same procedure for L=15, 13, 11, 9, 7, 5, 3 and 1 to get the remaining 64 basis images

Fig8

Fig9

19Slide20

BASIS IMAGES FOR MODE4 D-DCT

FOR 4X420

Diagonal Down RightSlide21

Basis Images for 8X8 Mode4 D-DCT

21DiagonalDownRightSlide22

Directional DCT – Mode 5

Fig10: The first 1D DCT along the vertical down right direction.

8X8 image block in which the first 1D DCT will be performed along the diagonal down-right direction.

These coefficients are arranged vertically as shown in Fig11.

1D

DCT horizontally with lengths

L=9, 9, 9, 9, 7, 7, 7 and 7

Fig11: The second 1D

DCT horizontally

4 8 8 8 8 8 8 8

DCT of Length

4

DCT of Length

22

9

9

9

9

7

7

7

7

(Vertical Down Right)

DCT of LengthSlide23

TO GET BACK THE ORIGINAL IMAGE ( INVERSE DIRECTIONAL DCT ) :

1D IDCT horizontally with lengths L=15, 13, 11,9,7,5,3,1Put back the coefficients in the Fig1 for 8X8 block. 1D IDCT directionally as shown in Fig1 and put back the coefficients in the same order. The output image is same as the original image.

DIRECTIONAL DCT MODE

5

OUTPUT

23

Mode5 Vertical Down RightSlide24

BASIS IMAGES FOR MODE5

Fig1: Horizontal IDCT

Fig2: 1D IDCT along vertical down right

Keep the 1

st

coefficient 1 and the remaining zero. Compute IDCT horizontally.

Put back the coefficient in the Fig2 vertical down-right.

Compute 1D IDCT along the vertical down-right direction and put back the coefficients in the same order back into the block.

The resulting block is 1 basis imageRepeat the same steps with the second coefficient as 1 and the remaining zero and computing IDCT horizontally and vertical down left. The output thus

obtained is 2nd basis image.Repeat the same procedure for L=

15, 13, 11, 9, 7, 5, 3 and 1 to get the remaining 64 basis images 249

9

9

9

7

7

7

7

IDCT of Length

4 8 8 8 8 8 8 8

IDCT of LengthSlide25

BASIS IMAGES FOR

4X4 MODE5 D-DCTFOR 4X4

25

(Vertical Down Right)Slide26

Basis Images for 8X8 Mode5 D-DCT

26(Vertical Down Right)Slide27

Forward Directional DCT:

For the directional modes, the first 1D DCT is applied along the direction of the dominant edge in each block. The second 1D DCT is along the horizontal direction in the rearranged pattern of the block.Inverse Directional DCT:To reconstruct the block, the first Inverse-DCT is applied along the horizontal direction.

The second Inverse-DCT is applied along the direction of the dominant edge in the block.

Procedure for obtaining the Directional DCT of a block and its reconstruction for MODES 6, 7 and 8:

27Slide28

ZIG-ZAG SCANNING

Fig12: Arrangement of coefficients after the second DCTFig13: Modified zigzag scanning

Figure13 shows all the coefficients (after the horizontal DCT) are shifted to the left.ZigZag

scanning is done after the second DCT shown in fig12.

Scanning is performed to group low frequency coefficients in top of vector

It performs quantization to round off most of the coefficients to zero or to

the nearest level.

28

8X8 Block

Mode3 Diagonal Down LeftSlide29

RESEARCH AREAS

Develop a directional DCT framework and demonstrate that it is able to provide a remarkable coding gain as compared to the conventional DCTEmbedded Directional DCT framework into H.264 [10] so that the corresponding directional DCT mode will be applied to an image block in combination with the best intra prediction chosen for this block.How to independently select the best DCT mode effectively.Directional DCTs can be extended to many existing international standards (for image and video coding)[10][11][12] that employ the conventional DCT.By selecting the best suited one from seven directional modes for each image block, it can be demonstrated that a remarkable coding gain is achieved in the

rate-distortion coding performance.Explore some other

zig-zag

scanning patterns appropriate for a particular directional mode leading to reduced bit count

29Slide30

Directional-Discrete Cosine Transform (D-DCT)

While D-DCT appears to provide remarkable coding gain compared to traditional DCT, the former inherently involves additional implementation complexity. This complexity factor needs to be explored fully. Trade off between the coding gain and additional complexity needs to be taken into account. 30Slide31

REFERENCES

F. Kamisli and J. S. Lim, “Video compression with 1-d directional transforms in H.264/AVC”, IEEE ICASSP, pp-738-741, March 2010. J. J. Fu and B. Zeng, “Directional discrete cosine transforms for image coding”, Advances in Multimedia Information Processing- PCM06, pp. 150-158, 2006.B. Zeng and J. J. Fu, “Directional discrete cosine transforms for image coding”, IEEE ICME, pp.721-724, July 2006. J. J. Fu and B. Zeng, “Directional discrete cosine transforms: a theoretical analysis,” IEEE ICASSP, vol.1, pp.1105-1108, April 2007.

B. Zeng and J. J. Fu, “Directional discrete cosine transforms- a new framework for image coding”, IEEE Trans. CSVT, vol. 18, pp. 305-313, March 2008.

A.

Dremeau

et al, “Sparse optimization with directional DCT bases for image compression”, IEEE ICASSP, pp.1290-1293, Dallas,

Tx, March 2010. C. L. Chang and B.

Girod, “Direction-adaptive partitioned block transform for image coding”, IEEE International Conference on Image Processing (ICIP08), pp.145-148, Oct. 2008.

H. Xu, J. Z. Xu and F. Wu, “Lifting-based directional DCT-like transform for image coding”, IEEE Trans. CSVT, vol.17, pp. 1325-1335, July 2007.

K. R. Rao and P.Yip, “Discrete Cosine Transform”, Boca Raton, FL: Academic Press, 1990.

31Slide32

A. Puri, X. Chen and A. Luthra, “Video coding using the H.264/MPEG-4 AVC compression standard”, Signal Processing: Image Communication, vol. 19, pp. 793-849, Oct. 2004.

11. L. Yu et al, “Overview of AVS video coding standards,” Signal Processing: Image Communication, vol. 24, pp. 263-276, April 2009.12. G. K. Wallace, “The JPEG still picture compression standard,” Communication of the ACM, vol. 34, pp. 31-44, April 1991.32