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Joint Optimization of Data Hiding and Video Compression

Joint Optimization of Data Hiding and Video Compression. Jithendra K. Paruchuri & Sen-ching S. Cheung Department of Electrical and Computer Engineering Center for Visualization and Virtual Environments University of Kentucky, Lexington, KY 40507 ISCAS - May 21, 2008. Overview.

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Joint Optimization of Data Hiding and Video Compression

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  1. Joint Optimization of Data Hiding and Video Compression Jithendra K. Paruchuri & Sen-ching S. Cheung Department of Electrical and Computer Engineering Center for Visualization and Virtual Environments University of Kentucky, Lexington, KY 40507 ISCAS - May 21, 2008

  2. Overview • Motivation and Problem • Data Hiding Framework • Rate-Distortion Optimized Data Hiding • Results • Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

  3. Signal Privacy • Smart video surveillance • Biometric theft • Mobile-media processing • RFID tracking

  4. Identity Obfuscation Original Black Box Pixelation/ Blurring Object Removal - Segmentation + Video In-painting [Venkatesh 06, 08]

  5. Problem with Obfuscation Police: Where were you 9am on Oct 1? A: I was in my office. Police: Do you have any proof? A: …… • Obfuscation destroys the authenticity • Original needed to legitimize the modification. • Accessed with proper authorization.

  6. Privacy Data Preservation • Separate Files or Meta-data • Cryptographic Scrambling [Boult05], [Dufaux06] • Data Hiding in DCT [Zhang05] • Works with any obfuscation techniques • High capability and low distortion • Fragile embedding • Eight-fold increase in output bit-rate!

  7. Parity Embedding Last decoded frame DCT Perceptual Mask • DCT Domain • Frequency, contrast and • luminance masking [Watson] Data Hiding with Compression DCT Entropy Coding Motion Compensation www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

  8. Embedding & Perceptual Distortion • To embed x in a quantized DCT coeff. c(i,j,k) • Select coefficients to minimize distortion • Contrast masking • Frequency masking • Distortion

  9. Causes of Bit-rate Explosion • Disturbing the ‘favorable characteristics’ (zero blocks & long run-lengths) for entropy coding • Data embedding inserts noise into motion compensation loop • Proposed solution: Identify specific DCT coefficients for data hiding that minimizes both the output rate and distortion www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

  10. R-D optimized Data Hiding Parity Embedding Last decoded frame Positions of the “optimal’ DCT coeff for embedding DCT R-D Optimization Perceptual Mask • DCT Domain • Frequency, contrast and • luminance masking [Watson] DCT Entropy Coding Parity Embedding Motion Compensation H.263 H.263 www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

  11. Constrained Optimization Let Rk(Mk) and Dk(Mk) be the rate and distortion after hiding Mk bits into the k-th DCT block. δ is a user-defined weight Optimization Problem:

  12. Calculations of Rk(Mk) and Dk(Mk) • Two Issues: • Parity embedding depends on hidden data • Need to find optimal selection as well • “Worst-case” embedding on previous frame • Optimal selection • Dk(Mk) is additive (easy) • Rk(Mk) is not: Rk(N) and Rk(N+1) may use very different coefficients

  13. Dynamic Programming versus Greedy approach • Dynamic Programming • Greedy Approximation • Pick next coefficient to minimize cost • Fast implementation i i+1 i+1 i+2 i+2 i+3 i+3 Embedding K-th bit Embedding K+1-st bit

  14. Performance Comparison • For CIF, Greedy needs 26 second/frame vs. DP needs 22 minutes/frame

  15. Dual of the optimization • Lower bounded by unconstrained opt: • Search λ to meet constraint • Start at 2nd order approximation of Ck(Mk) • 3-5 seconds per one CIF frame

  16. Experiment 1: Hall Monitor

  17. Hall Monitor (QP=10) www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

  18. Hall Monitor (QP=10) Original Distortion Optimized Weight = 0.5 Rate Optimized

  19. Surveillance Video

  20. Surveillance (QP=10) www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

  21. Surveillance (QP=10) Original Rate Optimized Distortion Optimized Weight=0.5

  22. Conclusions • Privacy Data Preservation with Data Hiding • R-D Optimization Framework for Data Hiding • Current work • Reversible Data Embedding: ICIP 2008 • Privacy Data Management: ICIP 2008 • Incorporate temporal dimension in perceptual and rate model • Joint encryption and data hiding www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

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