Multiple-description iterative coding image watermarking

Source:Authors:Reporter:Date:

Digital Signal Processing, Vol. 20, No. 4, pp.1183-1195, 2010Ying-Fen Hsia, Jan-Ray LiaoLu, Wan-Yu2012/12/03

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Outline

• Introduction• Related works

– Multiple-description coding

• Multiple-description iterative coding– Encoder

(Independent-turbo-coded multiple-description)– Decoder– Gray code

• The proposed watermarking system • Experimental results• Conclusions

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Introduction (1/2)

• The protection of the digital images becomes more and more important because they can be easily copied and modified on Internet.

• Digital watermarking techniques are required in the transfer procedure to ensure copyright protection.– Robustness is the most important characteristics in

a watermarking algorithm.

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Introduction (2/2)

• Multiple watermarks– several different watermarks – repeating the same watermark

• The multiple watermarks embedding capacity in an image is usually very limited.– the size of the watermark– collusion attacks

• Multiple-description coding.

Be useful against geometric distortion.

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• Multiple-description coding (多重描述編碼 )

– Separate signal into 2 correlated descriptions.

– Size of 2 descriptions < 2×original image

– Both descriptions available → error-free signal (無誤差 )

– Only one description available → slightly distorted signal (些微誤差 )

– Add error-correcting codes (錯誤修正碼 )

(This error correcting technique is called “Iterative decoding of multiple descriptions”)

Related work (1/3)

It saves the transmission bandwidth.

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Related work (2/3)

• Multiple-description coding (多重描述編碼 )

Single source

Two correlated bits streams

Transmitted

output

Fig.1. Block diagram for multiple-description code.

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Related work (3/3)

• Multiple-description coding (多重描述編碼 )

Fig.2. (a) MN index assignment matrix and (b) ML index assignment matrix.

0 1 2 3 4 5 6 7

0 0 1

1 2 3 5

2 4 6 7

3 8 9 10

4 11 13

5 12 14 15

6 16 17 19

7 18 20

(b) Modified Linear (ML)

Index i

Index j

0 1 2 3 4 5 6 7

0 0 2

1 1 3 4

2 5 6 8

3 7 9 10

4 11 12 14

5 13 15 16

6 17 18 20

7 19 21

(a) Modified Nested (MN)

Index i

Index j

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Multiple-description iterative coding

• Encoder (1 interleaver + 2 convolutional encoders)

Fig.3. MDIC encoder.

N bits

Inputs

First index(description)

Second index(description)

Outputs2 bits blocks

Coding rate: 1/2

(1/5)

交錯器

迴旋乘積編碼器

9Fig.4. Independent-turbo-coded multiple-description encoder.

Multiple-description iterative coding (2/5)

• Independent-turbo-coded multiple-description (2 interleavers + 4 convolutional encoders)

Coding rate: 1/2

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Fig.5. MDIC decoder.

• Decoder (2 MAP decoders + 1 interleaver)

Multiple-description iterative coding (3/5)

This whole process works iteratively until the solution is found.

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0 1 2 3 4 5 6 7

0 0 2

1 1 3 4

2 5 6 8

3 7 9 10

4 11 12 14

5 13 15 16

6 17 18 20

7 19 21

Fig.6. Index assignment.

Index pair (6,0)

When look up in the central matrix only, its nearest neighbor is (3, 2) or (4, 3) which corresponds to an output value of 8 or 10.

Multiple-description iterative coding (4/5)

• In a noisy environment, the index pair may falls at a grid where no value is assigned in the index assignment matrix.

12Fig.7. The effect of gray code on index assignment.

• To add gray code (格雷碼 ) to MDIC The lookup in the matrix is wrapped around.

(6, 0) → (101, 000)→ (101, 100) → (6, 7) → output value of 19

Multiple-description iterative coding (5/5)

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• Inter-block frequency-hopping spread spectrum watermark (IFHSS) 跨方塊跳頻展頻

– Frequency-hopping image watermark is inspired by the frequency-hopping spread spectrum (FHSS) communication.

– FHSS sends its message by repeating the same bit in several randomly selected frequency bands.

The proposed watermarking system (1/6)

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• Inter-block frequency-hopping spread spectrum watermark (IFHSS) 跨方塊跳頻展頻– Step1: Divide an image into 8x8 blocks and transformed

them by DCT.

– Step2: Randomly select a number of DCT coefficients.

– Step3: Compare DCT coefficients with JPEG luminance quantization table.

(Locations of non-zero quantized → candidate list)

The proposed watermarking system (2/6)

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• Inter-block frequency-hopping spread spectrum watermark (IFHSS) 跨方塊跳頻展頻– Step4: Randomly select 3 locations from the candidate

list → embedding location list.

– Step5: Not enough candidate in some blocks (Randomly add coefficients from neighboring blocks)

– Step6: Embedding location list → reshuffled (Watermark bit embedded into the location in the list)

The proposed watermarking system (3/6)

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• An example of embedding locations for IFHSS

The proposed watermarking system

1. Embed 6 bits in six image blocks.

2. Each bit is to be repeated 3 times.

3. 6x3=18 bedding locations. (squares)Reshuffle

Inter-block跨方塊

(4/6)

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• The watermark bit embedded into the selected location

The proposed watermarking system

Embedding Extraction α = 0.3 Xi = +1 (bit 1) Xi = -1 (bit 0)---------------------------------

embed: 0110--------------------------------- (0) V’=1(1+0.3×-1)=0.7 (1) V’=2(1+0.3×1)=2.6 (1) V’=3(1+0.3×1)=3.9 (0) V’=4(1+0.3×-1)=2.8

Subtract watermark block with the original block. (At each DCT location selected for embedding.) If Difference + : 1 - : 0--------------------------------

0.7-1=-0.3(0) 2.6-2=0.6 (1) 3.9-3=0.9(1) 2.8-4=-1.2(0) extract: 0110--------------------------------

)1(' iXVV

DCT coefficient

AFTER embedding

Strength

±1

DCT coefficient

BEFORE embedding

(5/6)

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The proposed watermarking system

Fig.8. Complete watermarking system.

• MDIC = multiple-description coder + iterative decoder

(6/6)

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Experimental results (1/5)• Number of embedded bits: 1024• Generator matrix for turbo code:• Index assignment for multiple description: MN matrix

• Tested 6 images 512x512 - 256 gray level:

(a) Lena (b) Fishing boat (c) Tank

(d) Couple (e) Mandrill (f) Stream and bridge

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Experimental results (2/5)

Fig.9. The average BER vs. PSNR for all the images.

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Experimental results (3/5)

Fig.10. BER vs. PSNR for (a) Lena, (b) fishing boat, (c) tank, (d) couple.

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Experimental results (4/5)

Fig.11. BER vs. PSNR for (e) mandrill and (f) stream and bridge.

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Experimental results (5/5)

Fig.12. BER with and without gray code vs. PSNR.

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Conclusions

• To add error-correction codes to multiple-description coding.

• MDIC compared to independent-coded system:– Better performance. – Low complexity.

• MDIC is a very good solution for apply multiple-description coding in image watermarks.

Thanks for your attention !

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Appendix

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Appendix

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Appendix

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Appendix

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Appendix