Multidescription video streaming with optimized reconstruction-based DCT and neural-network compensations

Packet and compression losses are two sources of quality losses when streaming compressed video over unreliable IP networks, such as the Internet. In this paper, we propose two new approaches for concealing such losses. First, we present a joint sender-receiver approach for designing transforms in multidescription coding (MDC). In the receiver, we use a simple interpolation-based reconstruction algorithm, as sophisticated concealment techniques cannot be employed in real time. In the sender we design an optimized reconstruction-based discrete cosine transform (ORB-DCT) with an objective of minimizing the mean squared error, assuming that some of the descriptions are lost and that the missing information is reconstructed by simple averaging at the destination. Second, we propose artificial neural network to compensate for compression losses introduced in MDC. Experimental results show that our proposed algorithms perform well in real internet tests