A blind video watermarking algorithm robust to lossy video compression attacks based on generalized Newton complex map and contourlet transform

The rapid growth of fast communication networks for digital video transmission has created a need to copyright protection for these media. Digital video can be manipulated easily by users with various motivations. Compression is the most common attack that users can apply on videos in order to elimi...

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Bibliographic Details
Published in:Multimedia tools and applications 2020, Vol.79 (3-4), p.2127-2159
Main Authors: Jafari Barani, Milad, Ayubi, Peyman, Yousefi Valandar, Milad, Yosefnezhad Irani, Behzad
Format: Article
Language:English
Subjects:
Algorithms
Communication networks
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Digital video
Embedding
Encryption
Multimedia Information Systems
Pseudorandom
Random numbers
Robustness
Singular value decomposition
Special Purpose and Application-Based Systems
Two dimensional models
Video communication
Video compression
Video transmission
Watermarking
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Summary:The rapid growth of fast communication networks for digital video transmission has created a need to copyright protection for these media. Digital video can be manipulated easily by users with various motivations. Compression is the most common attack that users can apply on videos in order to eliminate digital video copyright. Proposed technique in this article is specially designed for resisting against compression attacks. This method is presented a blind and robust watermarking method to copyright protection in digital video. In the proposed method, the coefficients of the contourlet transform are extracted and then encrypted watermark embedded into video with using the singular value decomposition (SVD). Embedding watermark in SVD domain increases the robustness of proposed method against attacks. In the embedding process and watermark encryption, pseudo-random numbers generated by the proposed new chaotic map, which is a generalized two-dimensional complex map based on the Newton model. The PSNR, SSIM, BER, and NCC measures examine the performance of the proposed method in terms of robustness and visual quality.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-019-08225-5