scholarly journals A Novel Blind and Robust Video Watermarking Technique in Fast Motion Frames Based on SVD and MR-SVD

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Imen Nouioua ◽  
Nouredine Amardjia ◽  
Sarra Belilita
Keyword(s):  
Singular Value Decomposition ◽  
Video Quality ◽  
Singular Value ◽  
Video Watermarking ◽  
Digital Video Watermarking ◽  
Video Frames ◽  
Fast Motion ◽  
Good Transparency ◽  
Value Decomposition

In this work, a novel and efficient digital video watermarking technique based on the Singular Value Decomposition performed in the Multiresolution Singular Value Decomposition domain is proposed. While most of the existing watermarking schemes embed the watermark in all the video frames, which is time-consuming and also affects the perceptibly of the video quality, the proposed method chooses only the fast motion frames in each shot to host the watermark. In doing so, the number of frames to be processed is consequently reduced and a better quality of the watermarked video is also ensured since the human visual system cannot notice the variations in fast moving regions. The watermark information is embedded by Quantization Index Modulation which is a blind watermarking algorithm. The experimental results demonstrate that the proposed method can achieve a very good transparency, while being robust against various kinds of attacks such as filtering, noising, compression, and frame collusion. Compared with several methods found in the literature, the proposed method gives a better robustness.

scholarly journals Observation Strategies Based on Singular Value Decomposition for Ocean Analysis and Forecast

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3445
Author(s):  
Maria Fattorini ◽  
Carlo Brandini
Keyword(s):  
Singular Value Decomposition ◽  
Maximum Error ◽  
Ocean Model ◽  
Singular Value ◽  
Practical Applications ◽  
Positioning Strategy ◽  
Value Decomposition ◽  
Observation Strategies

In this article, we discuss possible observing strategies for a simplified ocean model (Double Gyre (DG)), used as a preliminary tool to understand the observation needs for real analysis and forecasting systems. Observations are indeed fundamental to improve the quality of forecasts when data assimilation techniques are employed to obtain reliable analysis results. In addition, observation networks, particularly in situ observations, are expensive and require careful positioning of instruments. A possible strategy to locate observations is based on Singular Value Decomposition (SVD). SVD has many advantages when a variational assimilation method such as the 4D-Var is available, with its computation being dependent on the tangent linear and adjoint models. SVD is adopted as a method to identify areas where maximum error growth occurs and assimilating observations can give particular advantages. However, an SVD-based observation positioning strategy may not be optimal; thus, we introduce other criteria based on the correlation between points, as the information observed on neighboring locations can be redundant. These criteria are easily replicable in practical applications, as they require rather standard studies to obtain prior information.

scholarly journals Singular value automata and approximate minimization

2019 ◽  
Vol 29 (9) ◽  
pp. 1444-1478 ◽  
Author(s):  
Borja Balle ◽  
Prakash Panangaden ◽  
Doina Precup
Keyword(s):  
Singular Value Decomposition ◽  
Finite Rank ◽  
Singular Value ◽  
Linear Operators ◽  
Hankel Matrices ◽  
Weighted Automata ◽  
Approximate Minimization ◽  
Value Decomposition ◽  
Svd Decomposition

AbstractThe present paper uses spectral theory of linear operators to construct approximatelyminimal realizations of weighted languages. Our new contributions are: (i) a new algorithm for the singular value decomposition (SVD) decomposition of finite-rank infinite Hankel matrices based on their representation in terms of weighted automata, (ii) a new canonical form for weighted automata arising from the SVD of its corresponding Hankelmatrix, and (iii) an algorithmto construct approximateminimizations of given weighted automata by truncating the canonical form.We give bounds on the quality of our approximation.

Design of Digital Video Watermarking Technique Based on Motion Frames

2019 ◽  
Vol 16 (10) ◽  
pp. 4328-4338
Author(s):  
Purnima ◽  
Rakesh Ahuja
Keyword(s):  
Digital Technology ◽  
Digital Video ◽  
Heuristic Method ◽  
Singular Value ◽  
Video Watermarking ◽  
Discrete Wavelet ◽  
Original Video ◽  
Digital Video Watermarking ◽  
Multimedia Object ◽  
Value Decomposition

The availability of high internet bandwidth instantaneously transfer the digital video multimedia object between two or work workstations. Additionally, the advent of digital technology can be mistreating by malicious user to replicate multiple identical copies of the original video illegally. These capabilities introduce the issue of developing the methods for protecting the copyright of video multimedia objects. The proposed technique suggested detecting the motion part of the video by applying heuristic method of histogram difference between two consecutive frames. Then powerful transformations, Singular Value Decomposition (SVD), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are used to insert the different segment of the scrambled watermarks into different motion frames of the video. The experimental results show that the scheme is robust to unintentional and intentional video specific attacks which considered being frequently occurring attacks. The proposed algorithm has been contrasted with an existing DWT, DCT or hybrid-based approaches and is found to exhibit better robustness.

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