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HD video gives a realistic and life like subjective viewing experience and this becomes a major area of research in television broadcasting, video streaming or video transmission technology. To improve existing video standards and its coding efficiency of multi-view video sequences, the Joint Video Team (JVT) introduced multi-view video coding (MVC) that is extended and prolonged by H.264/AVC (Zeng et al., 2014; Kuan et al., 2014).
In video broadcast and movie production sections, there is a necessity for digital cameras that execute at various levels of performance and at different video compression standards. Run and gun, or compact, mobile cameras need fewer functions and a low cost, digital news gathering, studio, or second unit cameras require intermediate functionality. A cinema-grade camera requires the highest level of performance and functionality, hence error correction and prediction play very important role is video coding.
The elimination of spatial and temporal redundant video content reduces the amount of data when the compression gets done through a data transmission. Traditional/recent video compression scheme (say AVC H.264 and HEVC) focus more on utilization of channel capacity and compression ratio (Lie & Lin, 2013; Schuster et al., 2004). Due to this, reconstruction of the video data at the receiving end could be difficult and results lead to wrong prediction even if the channel is noise-free. When the channel is noisy and bit error rate is quite high, the reconstruction of video frames using common denoising technique will not able to match with the standards of video compression codec, this cause visually annoying video. The error resilience technique can reconstruct noise-free compressed video data at receiving end. This reconstruction is only up to certain extend and getting a completely noise free channel environment is practically not possible. Hence, the error concealment (EC) techniques are used. But traditional EC approaches may not work in all critical cases such as extremely noisy channel, fast /rapid moving pictures, etc.
EC, as a post processing method, recovers the lost blocks without modifying the encoder or channel coding schemes. The basic idea of EC is to estimate the corrupted blocks using correctly received blocks in the current video frame or adjacent frames. The reconstruction of video frames using EC can be classified into two approaches: Spatial error concealment (SEC) and temporal error concealment (TEC). SEC extract lost/corrupted information within the current frames only, which will not provide exact substitution of lost macro-blocks. Whereas TEC recovers lost information from previous or next video frames, while fetching the information for future frames. The system needs to hold the processes till the next frame reaches at the receiver end. This process further creates delay in the execution of the video transmission.
MPEG-4 has better compression features which has more probability of error propagation. The accuracy for the prediction of lost macro-block (MB) is needed to be improved. Boundary prediction and Motion Compensation can help to make EC approach more sound. Table 1 shows extensive literature review with their research gaps in more detail manner. MPEG-4 part-10 now referred as H.264 advance video codec scheme using variable length coding techniques, which promises a significant improvement over all previous video compression standards. The standard developed jointly by ITU-T and ISO/IEC supports video applications including low bit-rate wireless applications, standard-definition and high-definition broadcast television, video streaming over the internet, delivery of high-definition DVD content, and the highest quality video for digital cinema applications. With regard to error resiliency, MPEG-4 part 2 and H.264 both have resiliency tools available. H.264 has several “profiles” with different sets of features. The most common profile in use with high resolution video is “high profile”, which is biased towards higher compression, but does not allow all error resiliency tools. Not saying that this is a large disadvantage, but it’s just a fact of this codec. There are a couple of issues can be observed in H.264. First, because H.264 uses lossy compression like JPEG, there can be real issues with blurry text and colors that get changed for the worse during the encoding process. Obtained results will depend on the video content being encoded and the bit rate used by the encoder.