Research On Error Concealment Technology In Video Communication

Digital video communication can be found today in many application scenarios, such as broadcasting, wire-line and wireless real-time conversational services, Internet or LAN video streaming. One inherent problem with any communication system is that information may be altered or lost during transmission due to channel noise. The effect of such information loss can be devastating for the transport of compressed video, because any damage to the compressed bitstream may lead to objectionable visual distortion at the decoder. It is well-known that images of natural scenes have predominantly low frequency components, i.e. the color values of spatial and temporally adjacent pixels vary smoothly. These facts can be used to conceal the artifacts caused by transmission errors.All the error concealment techniques recover the lost information by making use of some a prior knowledge about the image/video signals, primarily the temporal, spatial and frequency smoothness property. This paper makes a study of typical error concealment algorithms by analyzing and performing simulations with the current release of the TML software, JM9.3 and a set of network simulation tools that are generally used by JVT.Recently, techniques for image reconstruction have gained popularity. The underlying idea is that the original image is modeled as a Markov random field (MRF) .Damaged parts are then reconstructed by maximum a posteriori (MAP) techniques. Selecting a proper neighborhood system and using the ability of Markov random field to describe spatial dependence, MRF can be used to model the structural and textural behavior of images. Selecting a appropriate model and making use of the optimal algorithm-simulated annealing to estimate the parameters, wonderful image restoration can be achieved. To evaluate the effectiveness of MRF based algorithms, this paper tests the algorithms by making a comparison of traditional approaches.