Adaptive Video Data Hiding through Cost Assignment and STCs

With the increasing popularity of digital video communication, video data hiding has become an active research topic in covert communication and privacy protection. Traditional video data hiding methods often use quantized discrete cosine transform (QDCT) coefficients to carry sufficient payload. However, since QDCT coefficients expose texture features and motion characteristics of the present video frame heavily, data embedding with QDCT coefficients may lead to significant intra-frame distortion and inter-frame distortion drift. To avoid obvious visual artifacts and keep bit-rate within a satisfactory level of the marked video, data embedding in QDCT coefficients should take into account both the intra-frame and inter-frame distortion impacts. It motivates the authors to propose an efficient cost assignment-based video data hiding method in this paper. The proposed cost assignment method aims to accurately evaluate the data embedding distortion. Specifically, the proposed scheme considers intra-frame changes and intra-frame distortion drift, for which the texture and motion changes of frames can be measured. The frame position is also used to reflect a cumulative distortion difference of multiple frames. For data embedding, syndrome-trellis code (STC) is adopted to minimize the overall distortion. Experimental results show that the proposed method significantly outperforms existing works in terms of payload-distortion performance.

[1]  Jinchang Ren,et al.  Cognitive Computation of Compressed Sensing for Watermark Signal Measurement , 2016, Cognitive Computation.

[2]  Xingming Sun,et al.  A video error concealment method using data hiding based on compressed sensing over lossy channel , 2018, Telecommun. Syst..

[3]  S. Srinivasan,et al.  Reversible data hiding in videos using low distortion transform , 2013, 2013 International Conference on Information Communication and Embedded Systems (ICICES).

[4]  Juan Zhao,et al.  Three-dimensional histogram shifting for reversible data hiding , 2018, Multimedia Systems.

[5]  Hang Zhou,et al.  Separable Reversible Data Hiding in Encrypted JPEG Bitstreams , 2018, IEEE Transactions on Dependable and Secure Computing.

[6]  Yun-Qing Shi,et al.  Separable Reversible Data Hiding for Encrypted Palette Images With Color Partitioning and Flipping Verification , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  Min-Shiang Hwang,et al.  A novel LSB data hiding scheme with the lowest distortion , 2017 .

[8]  Yue Li,et al.  Reversible Data Hiding with Low Bit-Rate Growth in H.264/AVC Compressed Video by Adaptive Hybrid Coding , 2016, ICCCS.

[9]  Mark R. Pickering,et al.  Video coding using fast geometry-adaptive partitioning and an elastic motion model , 2012, J. Vis. Commun. Image Represent..

[10]  Jicheng Wang,et al.  Prediction mode modulated data-hiding algorithm for H.264/AVC , 2010, Journal of Real-Time Image Processing.

[11]  Weiming Zhang,et al.  Decomposing Joint Distortion for Adaptive Steganography , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[12]  Hong Zhang,et al.  Covert Communication by Compressed Videos Exploiting the Uncertainty of Motion Estimation , 2015, IEEE Communications Letters.

[13]  Zhenxing Qian,et al.  Reversible Data Hiding in Encrypted JPEG Bitstream , 2014, IEEE Transactions on Multimedia.

[14]  Yong Liu,et al.  An adaptive data hiding algorithm with low bitrate growth for H.264/AVC video stream , 2017, Multimedia Tools and Applications.

[15]  Yun Q. Shi,et al.  PPE-Based Reversible Data Hiding , 2016, IH&MMSec.

[16]  Mark R. Pickering,et al.  Video Coding Using Elastic Motion Model and Larger Blocks , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[17]  Zhenxing Qian,et al.  New Framework of Reversible Data Hiding in Encrypted JPEG Bitstreams , 2019, IEEE Transactions on Circuits and Systems for Video Technology.

[18]  Jessica J. Fridrich,et al.  Minimizing embedding impact in steganography using trellis-coded quantization , 2010, Electronic Imaging.

[19]  Zhenxing Qian,et al.  On Improving Distortion Functions for JPEG Steganography , 2018, IEEE Access.

[20]  C. A. Burbeck,et al.  Spatiotemporal characteristics of visual mechanisms: excitatory-inhibitory model. , 1980, Journal of the Optical Society of America.

[21]  J. Mielikainen LSB matching revisited , 2006, IEEE Signal Processing Letters.

[22]  Shao-Yi Chien,et al.  Combination of SSIM and JND with content-transition classification for image quality assessment , 2012, 2012 Visual Communications and Image Processing.

[23]  Hanzhou Wu Minimizing Embedding Distortion with Weighted Bigraph Matching in Reversible Data Hiding , 2017, ArXiv.

[24]  Ke Niu,et al.  A Novel Video Reversible Data Hiding Algorithm Using Motion Vector for H.264/AVC , 2017 .

[25]  Ahmet Turan Özcerit,et al.  A new steganography algorithm based on color histograms for data embedding into raw video streams , 2009, Comput. Secur..

[26]  Shervin Shirmohammadi,et al.  A high capacity data hiding algorithm for H.264/AVC video , 2015, Secur. Commun. Networks.

[27]  Ingemar J. Cox,et al.  Secure spread spectrum watermarking for multimedia , 1997, IEEE Trans. Image Process..

[28]  Sung-Min Kim,et al.  Data Hiding on H.264/AVC Compressed Video , 2007, ICIAR.

[29]  Murat Kunt,et al.  Characterization of human visual sensitivity for video imaging applications , 1998, Signal Process..

[30]  Yun Q. Shi,et al.  Dynamic content selection-and-prediction framework applied to reversible data hiding , 2016, 2016 IEEE International Workshop on Information Forensics and Security (WIFS).

[31]  Weiming Zhang,et al.  Inter-frame distortion drift analysis for reversible data hiding in encrypted H.264/AVC video bitstreams , 2016, Signal Process..

[32]  Jessica J. Fridrich,et al.  Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes , 2011, IEEE Transactions on Information Forensics and Security.

[33]  Jiangqun Ni,et al.  New Distortion Metric for Efficient JPEG Steganography Using Linear Prediction , 2015, J. Signal Process. Syst..

[34]  Xiaojing Ma,et al.  A Data Hiding Algorithm for H.264/AVC Video Streams Without Intra-Frame Distortion Drift , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[35]  Hong Zhang,et al.  A Steganalytic Approach to Detect Motion Vector Modification Using Near-Perfect Estimation for Local Optimality , 2017, IEEE Transactions on Information Forensics and Security.

[36]  Weiming Zhang,et al.  A New Rule for Cost Reassignment in Adaptive Steganography , 2017, IEEE Transactions on Information Forensics and Security.

[37]  Oscal T.-C. Chen,et al.  Data hiding in inter and intra prediction modes of H.264/AVC , 2008, 2008 IEEE International Symposium on Circuits and Systems.