Search for: video-compression
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
Fast intra- and inter-prediction mode decision of H.264/AVC for medical frame compression based on region of interest, Article Australian Journal of Basic and Applied Sciences ; Volume 5, Issue 5 , 2011 , Pages 397-411 ; 19918178 (ISSN) ; Kasaei, S ; Sharif University of Technology
This paper aims at applying H.264/AVC in medical video compression applications and improving its compression performance with higher perceptual quality and lower coding complexity. We propose a new method that uses lossless compression in the region of interest (ROI) and very high rate lossy compression in other regions. The propose method achieves a fast intra- and interprediction mode decision that is based on encountering coarse MBs for intra- and inter- prediction mode decision of the background region and fine MBs for the ROI region. The MBs of the background region are encoded with the maximum quantization parameter allowed by H.264/AVC in order to maximize the number of null...
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
M.Sc. Thesis Sharif University of Technology ; Ghanbari, Mohammad
As the applications of digital video is becoming elementary parts of our daily life both in entertainment and business, the amount of digital video data being transferred by or stored in PDAs rapidly increases. Despite the fact that H.264/AVC is very efficient in terms of compression efficiency, however it is too complex to be used in devices in which their battery energy is restricted and cannot bear this complexity. In this thesis, a fast mode decision algorithm is proposed which brings into play the correlation in content of the video frames and reduces the number of candidate inter modes to be evaluated.For each macroblock, the proposed method performs two steps: first step attempts to...
Article Computers and Electrical Engineering ; Volume 35, Issue 4 , 2009 , Pages 536-548 ; 00457906 (ISSN) ; Kasaei, S ; Sharif University of Technology
In this paper, the problem of spatial error concealment for real-time applications is addressed. The proposed method can be categorized in exemplar-based error concealment approaches. In this category, a patch of corrupted pixels are replaced by another patch of the image that contains correct pixels. For splitting the erroneous block to different patches, a novel context-dependent exemplar-based algorithm based on a previously proposed segmentation method is proposed. The capability of the proposed method for concealment in diverse image regions is depicted. Our detailed conducted experiments show that the proposed method outperforms the state-of-the-art spatial error concealment methods in...
Article IEEE Transactions on Circuits and Systems for Video Technology ; Volume 26, Issue 4 , 2016 , Pages 627-635 ; 10518215 (ISSN) ; Karimi, M ; Marvasti, F ; Sharif University of Technology
In this paper, we present a compressive sampling and multihypothesis (MH) reconstruction strategy for video sequences that has a rather simple encoder, while the decoding system is not that complex. We introduce a convex cost function that incorporates the MH technique with the sparsity constraint and the Tikhonov regularization. Consequently, we derive a new iterative algorithm based on these criteria. This algorithm surpasses its counterparts (Elasticnet and Tikhonov) in recovery performance. Besides, it is computationally much faster than Elasticnet and comparable with Tikhonov. Our extensive simulation results confirm these claims
M.Sc. Thesis Sharif University of Technology ; Ghaemmaghami, Shahrokh
Owing to the unprecedented increasing rate of introducing new means of editing and transferring videos, appropriate and efficient methods for authentication and tampering detection are already playing a pivotal role in today's world. Amongst various methods for authentication, tampering detection and property right protection, the focus of this thesis is on watermarking. In the first place, we will present watermarking methods based upon H.264 standard. Due to the fact that almost all of the video products are stored and distributed in compressed file formats, the ability to retrieve the watermark after video compression is of crucial importance. Hence watermarking whilst video compression...
Article Proceedings - International Conference on Pattern Recognition, 23 August 2010 through 26 August 2010, Istanbul ; 2010 , Pages 4541-4544 ; 10514651 (ISSN) ; 9780769541099 (ISBN) ; Rabiee, H. R ; Pourdamghani, N ; Rohban, M. H ; Sharif University of Technology
We have developed a Gaussian Process Regression method with adaptive kernels for concealment of the missing macro-blocks of block-based video compression schemes in a packet video system. Despite promising results, the proposed algorithm introduces a solid framework for further improvements. In this paper, the problem of estimating lost macro-blocks will be solved by estimating the proper covariance function of the Gaussian process defined over a region around the missing macro-blocks (i.e. its kernel function). In order to preserve block edges, the kernel is constructed adaptively by using the local edge related information. Moreover, we can achieve more improvements by local estimation of...
Article 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016, 7 December 2016 through 9 December 2016 ; 2017 , Pages 1349-1353 ; 9781509045457 (ISBN) ; Marvasti, F ; IEEE Signal Processing Society; The Institute of Electrical and Electronics Engineers ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc 2017
Sparse signal processing has found various applications in different research areas where the sparsity of the signal of interest plays a significant role in addressing their ill-posedness. In this invited paper, we give a brief review of a number of such applications in inverse scattering of microwave medical imaging, compressed video sensing, and missing sample recovery based on sparsity. Moreover, some of our recent results on these areas have been reported which confirms the fact that leveraging the sparsity prior of the underlying signal can improve different processing tasks in various problems. © 2016 IEEE
M.Sc. Thesis Sharif University of Technology ; Sharifkhani, Mohammad
Digital video is one of the biggest part of digital data. The first step of digital video analytics is shot boundary detection. We used overlapped partitioning beside color histogram in uncompressed data and macroblock type prediction in compressed data as feature and supervised classifiers for decision making. Tests on TRECVID 2006 shows 8.9% improvement of F-measure in uncompressed video and 5.3% in h.264 bitstream. Supplementary test is done on IRIB dataset which shows 5.7% improvement of F-measure in uncompressed and 3.2% in H.264. H.264 based algorithm is almost 7 times faster in comparison to the algorithm that includes decoding
Article 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, 9 March 2008 through 11 March 2008 ; Volume 6 CCIS , 2008 , Pages 946-950 ; 18650929 (ISSN); 3540899847 (ISBN); 9783540899846 (ISBN) ; Rabiee, H. R ; Ghanbari, M ; Sharif University of Technology
In recent years, the demand for video transmission over wireless communication networks is growing very fast. The H.264 video compression standard which offers high quality at low bit rates, is a suitable codec for applications that require efficient video transmission over wireless networks. While the compressed videos are transmitted through error-prone networks, error robustness becomes an important issue. In this paper, a joint source-channel Lagrange optimization method in which the distortion of the decoder is estimated without using feedback which can be used for both multicast and point-to-point applications is proposed. The experimental results show that the new algorithm has a good...
Article 10th IEEE Singapore International Conference on Communications Systems, ICCS 2006, Singapore, 30 October 2006 through 1 November 2006 ; 2006 ; 1424404118 (ISBN); 9781424404117 (ISBN) ; Kasaei, S ; Sharif University of Technology
H.264/AVC, the latest video coding standard, achieves better video compression rates since it supports new features such as a large number of intra- and inter-prediction candidate modes. H.264/AVC adopts rate-distortion optimization (RDO) technique to obtain the best intra- and inter-prediction, while maximizing visual quality and minimizing the required bit rate. However, the RDO reduces the encoding speed via the exhaustive evaluation of all candidate modes. In this paper, we decrease the encoding time by reducing the computational complexity of the prediction function and the number of candidate modes. First, we improve Pan's method, by eliminating the DC mode from the candidates. Second,...