Conference/ProceedingsProc. of the Thirty-Ninth Asilomar Conference on Signals, Systems and Computers
Start date30.10.2005
End date02.11.2005
AddressPacific Grove, CA, USA
Pages874 - 878
Author(s)Sila Ekmekci Flierl, Thomas Sikora
TitleMulti-State Video Coding with Side Information
AbstractMulti-State Video Coding (MSVC) is a multiple description scheme where the video is splitted into two or more subsequences. Each subsequence is encoded and transmitted separately and can be decoded independently. The prediction
gain decreases due to sequence splitting but error resilience of the system increases since reconstruction capabilities improve. The lost frames in one subsequence are
reconstructed by using state recovery, i.e., interpolation of the past and/ future frames from the other subsequence. Unbalanced Quantized MSVC is realized by using the same
scheme but coding the subsequences with different quantization stepsizes yielding different bitrates. The advantage of unbalanced operation is the increased system performance in case of unbalanced transmission channel characteristics. In our previous work, we proposed an advanced reconstruction algorithm to support the unbalanced coding of the subsequences: State recovery is not only used for the lost frames but also for received frames when state recovery yields a higher frame PSNR than using the received packet and applying motion compensation. But to figure out which reconstruction method gives a higher frame PSNR a comparison with the original sequence is necessary. Therefore the method is applicable at the decoder only if a feedback mechanism between the encoder and decoder is present. In this work, we present an alternative way, MSVC with side information (MSVCSI), for guiding the optimized reconstruction stategy by estimating the reliabilities of several possible reconstruction alternatives. The reliabilty values are calculated recursively for each frame using the loss history of the frames and the side information representing the specific sequence characteristics. We show that under unbalanced transmission conditions, MSVCSI outperforms the original MSVC method (Approach 1) and the advanced MSVC (Approach 2) upto 1 dB depending on the loss rates of the transmission channels. The gain increases as the loss rates and the unbalance rate increase.
Key wordsmultiple description coding, optimal rate allocation, unbalanced quantization, path diversity