KEYWORDS: Video coding, Video, Automatic repeat request, Quantization, Forward error correction, Data compression, Distortion, Video processing, Signal attenuation, Computer programming
Multiple Description Video Coding (MDC) and Layered Coding (LC) are both error-resilient source coding techniques used for transmission over error-prone channels. Both techniques generate multiple streams. The streams generated by MDC correspond to different descriptions of the same source whereas the streams produced by LC are differentiated as base and enhancement layer streams. Moreover whereas the MDC streams are independently decodable the decoding of the enhancement layer stream is dependent on the decoding of the base layer stream. In this work we concentrate on specific MDC and LC schemes, i.e. Multi-State Video Coding (MSVC) and Temporal Layered Coding (TLC). MSVC was introduced by John Apostolopoulos and it was showed that if each frame is transmitted in a separate packet and if motion information for each lost frame is also lost, MSVC outperforms Single Layer Coding (SC) in recovering from single as well as burst losses. Here we compared MSVC with TLC as an extension of SC based on transmission simulations over lossy channels under the assumption that the motion vectors are always available. Using different coding modes and specific reconstruction methods average reconstructed frame PSNR (peak signal to noise ratio) is measured and compared. Results show that when motion vectors are received TLC performs better than MSVC for every coding option tested. The performance difference is bigger for low motion sequences.
Multiple State Video Coding (MSVC) is a Multiple Description Coding Scheme where the video is coded into multiple independently decodable streams, each with its own prediction process and state. The system subject to this work is composed of two subsystems: 1- multiple state encoding/decoding, 2- path diversity transmission system. In [1] we discussed how to optimize the rate allocation of such a system while maximizing the average reconstructed frame PSNR at the decoder and minimizing the PSNR variations between the streams given the total bitrate RT and the balanced (equal loss probabilities) or unbalanced (unequal) loss probabilities p1 and p2 over the two paths. In our current work we establish a theoretical framework to estimate the rate-(decoder) distortion (R-Dd) function and have taken into account the MSVC-structure, the rate allocation, channel impairments and reconstruction strategies respectively. The video sequence is modeld as an AR(1) source and the distortion associated with each reconstructed frame in both threads is a lossy transmission environment is estimated recursively depending on the system parameters.
Multiple Description Coding is a forward error correction scheme where two or more descriptions of the source are sent to the receiver over different channels. If only one channel is received the signal can be reconstructed with distortion D1 or D2. On the other hand, if both channels rae received the combined information is used to achieve a lower distortion D0. Our approach is based on the Multiple State Video Coding with the novelty that we achieve a flexible unbalance rate of the two streams by varying the quantization step size while keeping the original frame rate constant. The total bitrate Rτ is fixed which is to be allocated between the two streams. If the assigned bitratres are not balanced there will be PSNR variations between neighboring frames after reconstruction. Our goal is to find the optimal rate allocation while maximizing the average reconstructed frame PSNR and minimizing the PSNR variations given the total bitrate Rτ and the packet loss probabilities p1 and p2 over the two paths. The reconstruction algorithm is also taken into account in the optimization process. The paper will report results presenting optimal system designs for balanced but also for unbalanced path conditions.
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