Sharif Digital Repository

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... 

Multiple description coding (MDC) is a technique where multiple streams from a source video are generated, each individually decodable and mutually refinable. MDC is a promising solution to overcome packet loss in video transmission over noisy channels, particularly for real-time applications in which retransmission of lost information is not practical. A problem with conventional MDC is that the achieved side distortion quality is considerably lower than single description coding (SDC) quality except at high redundancies which in turn leads to central quality degradation. In this paper, a new mixed layer MDC scheme is presented with no degradation in central quality, and providing better... 

Multiple Description Coding (MDC) is a technique where multiple streams from a source are generated, each individually decodable and mutually refinable. In this paper, a new Mixed Layer MDC (MLMDC) scheme is presented which achieves a higher side quality compared to conventional MDCs. The improved side performance leads to higher average video quality at the receiver in lossy networks. For each DCT coefficient, we generate two coefficients: Base Coefficient (BC) and Enhancement Coefficient (EC) which are combined together. When all descriptions are available, they are decomposed and decoded to achieve high quality video. When one description is not available, we use estimation to extract as... 

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... 

In this paper we investigate multi-path transmission of video over Wireless Multimedia Sensor Networks (WMSNs). Our objective is to provide a transmission mechanism to improve the video quality perceived at the receiver while considering energy, bandwidth and delay constraints of the network. Our approach is based on packet and path priority scheduling in multipath video transmission over WMSN. Video packets are classified according to their types and more important packets are transmitted through paths with better conditions. Path conditions are evaluated by a score mechanism using variant parameters such as free buffer size, energy, hop count and packet loss. Since path conditions are...