Search for: motion-vectors
Article Entropy ; Volume 20, Issue 4 , 2018 ; 10994300 (ISSN) ; Faez, K ; Saffari Pour, M ; Sharif University of Technology
MDPI AG 2018
In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and...
Article Canadian Conference on Electrical and Computer Engineering; Technology Driving Innovation, 2004, Niagara Falls, 2 May 2004 through 5 May 2004 ; Volume 4 , 2004 , Pages 2021-2024 ; 08407789 (ISSN); 0780382536 (ISBN) ; Ghandi, M. M ; Shamsollahi, M. B ; Sharif University of Technology
In this paper a new context modelling scheme for arithmetic coding of Motion Vectors (MVs) is proposed. The model uses the correlation between the horizontal and vertical components of MVs to improve the probability estimation of symbols. The accurate probability estimation can therefore improve the efficiency of the context-based arithmetic coder. The proposed scheme has been adapted to the H.264 advanced video codec and the simulation results show that a considerable bit rate saving can be achieved in MV coding
Article Iranian Conference on Machine Vision and Image Processing, MVIP ; 2013 , Pages 43-47 ; 21666776 (ISSN) ; 9781467361842 (ISBN) ; Ghanei Yakhdan, H ; Kasaei, S ; Sharif University of Technology
IEEE Computer Society 2013
Error concealment is a useful method for improving the damaged video quality in the decoder side. In this paper, a dynamic method with low computational complexity is presented to improve the visual quality of videos when up to 50% of the frames are damaged. In the proposed method, temporal replacement and the improved outer boundary matching algorithm are used for dynamical error concealment in inter-frames of videos. With the use of motion vectors (MVs) which are close to the damaged macroblock (MB) the method can determine whether the motion in specific areas is either regular, irregular, or zero. Then, based on this knowledge, different methods are performed. It adaptively selects a set...
M.Sc. Thesis Sharif University of Technology ; Fatemizadeh, Emadoddin
In this research a novel method is proposed which uses the concept of image registration to forecast frames as a new frame up conversion method. This frame rate up conversion method is specially designed for medical videos because of the medical structure of the none rigid image registration used as a field to forecast new frames which causes better results for these kinds of videos. In this method we interpolate new frames in the field of none rigid transformation grid in order to improve video parameters such as blocking, blurriness, etc. which can help doctors to detect abnormalities in such videos much preciously. By analyzing existing methods, we can find that this field is bereft of a...
Article ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 22 May 2011 through 27 May 2011 ; May , 2011 , Pages 953-956 ; 15206149 (ISSN) ; 9781457705397 (ISBN) ; Bayati, A ; Rabiee, H. R ; Rohban, M. H ; Sharif University of Technology
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem of estimating the lost motion vectors is modelled as a kernel construction problem in a Bayesian framework. First, to describe the similarity between the neighboring motion vectors, a kernel function is defined. Then the parameters of the kernel function is estimated as the coefficients of a linear Bayesian estimator. The experimental results verify the superiority of the proposed algorithm over the conventional and state of the art motion vector concealment methods. Moreover, noticeable improvements on both...
M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza
Error concealment is one of the effective ways to alleviate the effect of packet loss in video communication over error-prone environments. In order to estimate lost macro-blocks, we have employed Bayesian estimation as an efficient and robust framework. Gaussian process regression has been used as the modeling approach through this framework. Considering luminance component as Gaussian process,a minimum mean squared error estimation of the lost macro-block is obtained. This estimator, as a function of the existing data, is only determined by the covariance matrix defined over them. Therefore,the main step in Gaussian process regression, is construction of the convenient covariance matrix...
Article Smart Innovation, Systems and Technologies ; Volume 11 SIST , 2011 , Pages 143-151 ; 21903018 (ISSN) ; 9783642221576 (ISBN) ; Pouladi, F ; Salehinejad, H ; Talebi, S ; Sharif University of Technology
Global motion estimation (GME) is an important technique in image and video processing. Whereas the direct global motion estimation techniques boast reasonable precision they tend to suffer from high computational complexity. As with indirect methods, though presenting lower computational complexity they mostly exhibit lower accuracy than their direct counterparts. In this paper, the authors introduce a robust algorithm for GME with near identical accuracy and almost 50-times faster than MPEG-4 verification model (VM). This approach entails two stages in which, first, motion vector of sampled block is employed to obtain initial GME then Levenberg-Marquardt algorithm is applied to the...
Article 2009 IEEE International Workshop on Imaging Systems and Techniques, IST 2009, Hong Kong, 11 May 2009 through 12 May 2009 ; 2009 , Pages 71-75 ; 9781424434831 (ISBN) ; Shirali Shahreza, S ; IEEE Instrumentation and Measurement Society ; Sharif University of Technology
Motion estimation (ME) is one of the key parts of video compression algorithms. But, motion estimation and computation of motion vectors (MVs) are very time con-suming. In this paper, we propose a method for reducing the cost of motion estimation process. During this process, a series of candidate blocks should be searched to find the best motion vectors. In our method, we compare the skin parts of two blocks before comparing all pixel pairs of the two blocks. Having a preprocessing phase, the skin part comparison is performed quickly. This method provides a parameter that can be used to create a balance between the processing time and the motion estimation accuracy. © 2009 IEEE
Article 2011 19th Iranian Conference on Electrical Engineering, ICEE 2011, 17 May 2011 through 19 May 2011 ; May , 2011 ; 9789644634284 (ISBN) ; Panahi, M. A ; Kasaei, S ; Sharif University of Technology
Due to fast growth of wireless mobile networks, video transmission over wireless media has been widely studied. As wireless networks are error prone, there is a high possibility of loss in sent packets. Since time limitations in real-time video applications should be met, the delay-related to resending packets is not acceptable and the error should to be concealed at receiver side. With respect to different concealment methods, two new methods for temporal error concealment are proposed. In the first method, an optimized set of motion vectors is formed using motion vectors in surrounding blocks of the lost macroblock, and then this set is searched for the best motion vector. For extending...
Article 4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010, Gold Coast, QLD, 13 December 2010 through 15 December 2010 ; 2010 ; 9781424479078 (ISBN) ; Mohammadiha, N ; Kasaei, S ; Sharif University of Technology
Low-complexity error concealment techniques for missing macroblock (MB) recovery based on the boundary matching principle are extensively studied and evaluated. In this paper, an improved boundary matching algorithm (BMA) using adaptive search is presented to conceal channel errors in inter-frames of video images. The proposed scheme adaptively selects proper candidate regions to conceal the artifact of a lost block. The candidate regions are examined based on analyzing motion activity of the neighboring MBs. Simulations show that the proposed scheme outperforms both on PSNR and visual quality obviously of about 1-4dB compared to existing methods