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1 Adjustable prediction-based reversible data hiding Authors: Chin-Feng Lee and Hsing-Ling Chen Source: Digital Signal Processing, Vol. 22, No. 6, pp.

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Presentation on theme: "1 Adjustable prediction-based reversible data hiding Authors: Chin-Feng Lee and Hsing-Ling Chen Source: Digital Signal Processing, Vol. 22, No. 6, pp."— Presentation transcript:

1 1 Adjustable prediction-based reversible data hiding Authors: Chin-Feng Lee and Hsing-Ling Chen Source: Digital Signal Processing, Vol. 22, No. 6, pp. 941–953, 2012

2 2 Outline Introduction Proposed method Experimental results Conclusions

3 3 Introduction Tseng and Hsieh’s scheme Prediction value (P) = ( )/2 = Proposed scheme

4 4 The proposed scheme- Embedding phase Cover image Threshold (T) = 0 01 Extra data: 0

5 5 The proposed scheme- Embedding phase Modified image T = 0 s = 1 C = 101 P = 101 d = 101 – 101 = 0 P’ = P + 2*d + s = * = d = 0 T = 0

6 6 The proposed scheme- Embedding phase Modified image T = 0 s = 1 C = 105 P = 76 d = 105 – 76 = 29 P’ = C + T + 1 = = d = 29 T = 0

7 7 The proposed scheme- Embedding phase Modified image T = 0 s = 1 C = 102 P = 76 d = 102 – 76 = 26 P’ = C + T + 1 = = d = 26 T = 0

8 8 The proposed scheme- Embedding phase Modified image T = 0 s = 1 C = 1 P = 104 d = 1 – 104 = –103 P’ = 1 – T – 1 = 1 – 0 – 1 = d = –103 T = 0

9 9 The proposed scheme- Extraction and recovery phase Stego image T’ = 2*T + 1 = = 1 P’ = 0 P = 104 d = 0 – 104 = –104 C = 0 + T + 1 = = d = – T’ = 1

10 10 The proposed scheme- Extraction and recovery phase Stego image T’ = 1 P’ = 103 P = 76 d = 103 – 76= 27 C = 103 – T – 1 = 103 – 0 – 1 = d = T’ = 1 0

11 11 The proposed scheme- Extraction and recovery phase Stego image T’ = 1 P’ = 106 P = 76 d = 106 – 76= 30 C = 106 – T – 1 = 106 – 0 – 1 = d = T’ = 1 0

12 12 The proposed scheme- Extraction and recovery phase Stego image T’ = 1 P’ = 102 P = 101 d = 102 – 101 = 1 s = d mod 2 = 1 C = P – d / 2 = 101 – 1 / 2 = d = T’ = 1 0

13 13 The proposed scheme- Extraction and recovery phase Modified image T’ = Extra data: 0

14 14 Experimental results 48.6 dB and 0.2 bpp 47.9 dB and 0.06 bpp dB and 0.99 bpp dB and 0.71 bpp

15 15 Experimental results

16 16 Experimental results- Lena

17 17 Experimental results- F-16

18 18 Experimental results- Baboon

19 19 Experimental results- Boats

20 20 Conclusions This study proposes a reversible data hiding scheme that exploits the adjustment of prediction-errors to increase the embedding rate and reduce image distortion. The proposed scheme exploits a threshold to achieve the flexibility in perceptual image quality and embedding.

21 21 Thank you.

22 22 Appendix [16] J. Tian, “Reversible data embedding using a difference expansion,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, pp , [17] Z. Ni, Y. Q. Shi, N. Ansari, and W. Su, “Reversible data hiding,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 16, pp , [19] W. L. Tai, C. M. Yeh, and C. C. Chang, “Reversible data hiding based on histogram modification of pixel differences,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 19, pp , 2009.

23 23 Appendix [20] D. M. Thodi and J. J. Rodriguez, “Expansion embedding techniques for reversible watermarking,” IEEE Transactions on Image Processing, Vol. 16, pp , [21] P. Tsai, Y. C. Hu, and H. L. Yeh, “Reversible image hiding scheme using predictive coding and histogram shifting,” Signal Processing, Vol. 89, pp , [22] K. S. Kim, M. J. Lee, H. Y. Lee, and H. K. Lee, “Reversible data hiding exploiting spatial correlation between sub-sampled images,” Pattern Recognition, Vol. 42, pp , 2009.

24 24 Appendix [25] Y. C. Liu, H. C. Wu, and S. S. Yu, “Adaptive DE- based reversible steganographic technique using bilinear interpolation and simplified location map,” Multimedia Tools and Applications, Vol. 52, pp , [26] C. F. Lee and H. L. Chen, “Reversible data hiding based on histogram modification of prediction- error,” Imaging Science Journal, Vol. 59, pp , [27] H. W. Tseng and C. P. Hsieh, “Prediction-based reversible data hiding,” Information Sciences, Vol. 179, pp , 2009.


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