Stanislav Marchevsky

Adaptive vector LUM smoother

A new vector approach, the adaptive vector LUM smoother for color images is presented. The novelty of the proposed method lies in the two-stages adaptive choice of the estimate, where in the first filter stage (N+1)/2 outputs with all smoothing levels done by the vector LUM smoother with window size N are generated. In the next filter stage, one of (N+1)/2 possible samples is adaptively selected to determine the filter output depending on the local information, by the filter window. Thus, the proposed method provides an optimal estimate in the sense of objective criteria. In addition, the filter output is constrained to be a sample from an input set that cannot result in color artifacts.

Bayesian filtering techniques: Kalman and extended Kalman filter basics

Bayesian filters provide a statistical tool for dealing with measurement uncertainty. Bayesian filters estimate a state of dynamic system from noisy observations. These filters represent the state by random variable and in each time step probability distribution over random variable represents the uncertainty. If estimate is needed with every new measurement, it is suitable to use recursive filter. Unfortunately optimal Bayesian solution exists in a restrictive set of cases, e.g. Kalman filters which assume Gaussian PDF or we need to use suboptimal solution, e.g. extended Kalman filters which use local linearization to approximate PDF to be Gaussian.

Temporal-spatial error concealment algorithm for intra-frames in H.264/AVC coded video

Video communication through wireless channels is still a major problem due to the limitations in bandwidth and the presence of channel errors. The other limitations within the mobile networks is low transmission bit rate which demands the reduction of the used video resolution and a high efficient video compression technique. Video transmission in wireless environments is a challenging task calling for high-compression efficiency as well as a network-friendly design. The network-friendly design of H.264/AVC is addressed via the network abstraction layer that has been developed to transport the coded video data over any existing and future networks including wireless systems. Exploiting this feature, we present a modified temporal-spatial error concealment algorithm for H.264 coded video. Simulations were carried out in computing environment Matlab using the standard video-sequences.

Error resilience tools in the MPEG-4 and H.264 video coding standards

In this paper we introduce error resilience tools which are used by MPEG-4 and H. 264 video coding standards. MPEG-4 as well as H.264 offers error resilience tools which were implemented by older video coding standards, but they also introduce new tools and improved efficiency of previously used tools. This paper offers only brief review of them, but it focuses on their most important characteristics.

Nonlinear noise estimation and compensation in GFDM based communication systems for cognitive radio networks

Generalized Frequency Division Multiplexing (GFDM) might be a promising candidate for deployment in cognitive radio networks and for 5G wireless communication. It is a non-orthogonal multicarrier modulation scheme based on flexible pulse shaping. However, given by the high signal amplitude fluctuation, the performance of GFDM systems is highly degraded due to the distortion caused by the nonlinear nature of high power amplifier (HPA). In this article, we investigate the effects of nonlinearities in GFDM and introduce an iterative receiver scheme to reduce the error probability of GFDM signals undergoing nonlinear amplification. The proposed technique is based on successive estimation and cancellation of the in-band distortion introduced by the nonlinear nature of the HPA characteristics. The performance improvement of the iterative receiver structure is expressed by the bit error performance and error vector magnitude.

A multi-view e-learning system for remote education

In this paper, a multi-view e-learning system for supporting remote education is introduced. Since video is the most natural way to perceive information and of interaction between people, it also has inherent capabilities when using in education environment. The system, we propose, should encourage students more use the opportunities offered by remote learning to foster their training on the university. To enable multi-view video (MVV) streaming a system with three cameras is used. A central server is used to capture the partial streams and it also serves as the control unit to manage the whole system. The student will have the choice to decide which particular part of the captured scene he/she wants to watch. Another option will be a guided stream, where the streams are switched automatically, based on the area where the presentation is currently focused. We believe that this model might contribute to the educational process.

Simulation of packet losses in video transfers using real-time transport protocol

Multimedia content transmitted over unreliable environment, like wireless channels or in generally any network with unreliable transport protocol, is always subject to packet loss due to network congestion and channel noise. By using compressed video, errors could propagate to the subsequent frames with resulting worse video quality. Therefore it is necessary to study impact of packet loss on overall video quality. First step in such study is creation of network models. The most popular approach is network modeling using Markov chains. In our paper we have analyzed in which way have occurred packet losses during transmission of video through wired and also wireless network.

Applying of video technologies in educational process

Nowadays, multiview video, as an advanced form of educational video, is in development phase. In this article, positive and problematic aspects of educational video are described from the point of view of a teacher. The technical properties and problems of multiview video streaming, such as Multiview Video Coding (MVC), streaming technology, and multiview video database systems are briefly mentioned. The realization phase of educational multiview video streaming is introduced, as well.

Cooperative spectrum sensing schemes for cognitive radios using dynamic spectrum auctions

In this paper, we tackle the spectrum allocation problem in cognitive radio networks with the combined solution using the cooperative spectrum sensing a and adaptive spectrum auction process. Different from all the previous work analyzing the traditional spectrum auction mechanisms, we introduce the spectrum sensing impairments resulting to the existence of the risk entering the spectrum auction process. The term risk reflects the situation when the fusion center based on the information from the secondary terminals participating on the cooperative spectrum access gives the permission to the terminals to transmit, but in fact there is still primary user active. This results in the collisions due to the false information entering the spectrum auction process. Due to the stochastic nature of the risk, the different decision logics of the distributed spectrum sensing algorithms provides different results. We analyze and, or and majority decision rules of the distributed spectrum access jointly with the sensitivity of the multiple unit sequential first-price sealed-bid auction spectrum auction against the false detection. The results demonstrate that in risky environment, total revenue and total payoff of the auctioneer and bidder respectively is lower, than in the case of system with lower level of risk.

TCP for wireless network

Video transmitted over error prone channel is always subject to packet losses. One way, how to deal with this problem is using connection-oriented, end-to-end reliable protocol. In this paper we focused on several implementations of transmission control protocol, which fulfill the conditions for reliable delivery of information. Tahoe, Reno and New Reno implementation supported by TCP are part of congestion avoidance mechanisms of the protocol suite. The main difference between them is mechanism of detection and reaction on the packet loss. Thus we have tried to evaluate their performance.