1. Multiple-description iterative coding image watermarking Source: Authors: Reporter: Date: Digital Signal Processing, Vol. 20, No. 4, pp.1183-1195, 2010 Ying-Fen Hsia, Jan-Ray Liao Lu, Wan-Yu 2012/12/03

2. 2 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

3. 3 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.

4. 4 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.

5. 5 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.

6. 6 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.

7. 7 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. 01234567 001 1235 2467 38910 41113 5121415 6161719 71820 (b) Modified Linear (ML) Index i Index j 01234567 002 1134 2568 37910 4111214 5131516 6171820 71921 (a) Modified Nested (MN) Index i Index j

8. 8 Multiple-description iterative coding Encoder (1 interleaver + 2 convolutional encoders) Fig.3. MDIC encoder. N bits Inputs First index (description) Second index (description) Outputs 2 bits blocks Coding rate: 1/2 (1/5) (1/5) 交錯器 迴旋乘積編碼器

9. 9 Fig.4. Independent-turbo-coded multiple-description encoder. Multiple-description iterative coding (2/5) (2/5) Independent-turbo-coded multiple-description (2 interleavers + 4 convolutional encoders) Coding rate: 1/2

10. 10 Fig.5. MDIC decoder. Decoder (2 MAP decoders + 1 interleaver) Multiple-description iterative coding (3/5) (3/5) This whole process works iteratively until the solution is found.

11. 11 01234567 002 1134 2568 37910 4111214 5131516 6171820 71921 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) (4/5) In a noisy environment, the index pair may falls at a grid where no value is assigned in the index assignment matrix.

12. 12 Fig.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) (5/5)

13. 13 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) (1/6)

14. 14 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) (2/6)

15. 15 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) (3/6)

16. 16 An example of embedding locations for IFHSS The proposed watermarking system 1. E mbed 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) (4/6)

17. 17 The watermark bit embedded into the selected location The proposed watermarking system EmbeddingExtraction 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 -------------------------------- DCT coefficient AFTER embedding Strength ±1 DCT coefficient BEFORE embedding (5/6) (5/6)

18. 18 The proposed watermarking system Fig.8. Complete watermarking system. MDIC = multiple-description coder + iterative decoder (6/6) (6/6)

19. 19 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

20. 20 Experimental results (2/5) Fig.9. The average BER vs. PSNR for all the images.

21. 21 Experimental results (3/5) Fig.10. BER vs. PSNR for (a) Lena, (b) fishing boat, (c) tank, (d) couple.

22. 22 Experimental results (4/5) Fig.11. BER vs. PSNR for (e) mandrill and (f) stream and bridge.

23. 23 Experimental results (5/5) Fig.12. BER with and without gray code vs. PSNR.

24. 24 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.

25. Thanks for your attention !

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