Robust Image Watermarking Based on Compressed Sensing Techniques

Compressed sensing is a newly developed topic in the field of data com- pression. Most of relating researches focus on compression performances or theoretical studies, and there are very few papers aiming at the integration of watermarking into compressed sensing systems. In this paper, we propose an innovative scheme that con- siders the copyright protection of data with compressed sensing. By carefully utilizing the relationships between compressively sensed coefficients, very few amounts of trans- mitted coefficients are capable of reconstructing the image to some extent. Moreover, secret information embedded beforehand can be recovered with acceptable rate in correctly extracted bits even experiencing through the lossy channels for delivery of marked image. Simulation results with our algorithm have demonstrated the effectiveness for integrating watermarking into compressive sampling systems.

[1]  Lei Liu,et al.  Adaptive Distributed Compressed Video Sensing , 2014, J. Inf. Hiding Multim. Signal Process..

[2]  Ying Lv,et al.  A New Compressed Sensing Algorithm Design Based on Wavelet Frame and Dictionary , 2014 .

[3]  Shu-Chuan Chu,et al.  Invariability of Mean Value Based Reversible Watermarking , 2013, J. Inf. Hiding Multim. Signal Process..

[4]  Jeng-Shyang Pan,et al.  Tabu search based multi-watermarks embedding algorithm with multiple description coding , 2011, Inf. Sci..

[5]  Stefano Tubaro,et al.  A compressive-sensing based watermarking scheme for sparse image tampering identification , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[6]  Jeng-Shyang Pan,et al.  Geometrically invariant image watermarking using Polar Harmonic Transforms , 2012, Inf. Sci..

[7]  Richard G. Baraniuk,et al.  Blind Error-Free Detection of Transform-Domainwatermarks , 2007, 2007 IEEE International Conference on Image Processing.

[8]  Ajith Abraham,et al.  Optimized Watermarking Using Swarm-Based Bacterial Foraging , 2010, J. Inf. Hiding Multim. Signal Process..

[9]  Jeng-Shyang Pan,et al.  Robust VQ-based digital watermarking for memoryless binary symmetric channel , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[10]  Constantinos Patsakis,et al.  LSB and DCT steganographic detection using compressive sensing , 2014, J. Inf. Hiding Multim. Signal Process..

[11]  Lamri Laouamer,et al.  New Images Watermarking Scheme Based on Singular Value Decomposition , 2013, J. Inf. Hiding Multim. Signal Process..

[12]  Gonzalo Mateos,et al.  Robust Nonparametric Regression via Sparsity Control With Application to Load Curve Data Cleansing , 2011, IEEE Transactions on Signal Processing.

[13]  Rong Huang,et al.  A Robust and Compression-Combined Digital Image Encryption Method Based on Compressive Sensing , 2011, 2011 Seventh International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[14]  J. Romberg,et al.  Imaging via Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[15]  Bu-Sung Lee,et al.  Robust Image Coding Based Upon Compressive Sensing , 2012, IEEE Transactions on Multimedia.

[16]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[17]  Trac D. Tran,et al.  Fast compressive sampling with structurally random matrices , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[18]  Hsiang-Cheh Huang,et al.  Metadata-based image watermarking for copyright protection , 2010, Simul. Model. Pract. Theory.

[19]  Jeng-Shyang Pan,et al.  High Capacity Watermark Embedding Based on Invariant Regions of Visual Saliency , 2011, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[20]  Jeng-Shyang Pan,et al.  Robust image watermarking based on multiple description vector quantisation , 2004 .

[21]  Hsiang-Cheh Huang,et al.  A Progressive Image Watermarking Scheme for JPEG2000 , 2012, 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.