A Unified Estimation-Theoretic Framework For Error-Resilient Scalable Video Coding
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
A novel scalable video coding (SVC) scheme is proposed for video transmission over lossy networks, which builds on an estimationtheoretic (ET) framework for optimal prediction and error concealment, given all available information from both the current base layer and prior enhancement layer frames. It incorporates a recursive end-to-end distortion estimation technique, namely, the spectral coefficient-wise optimal recursive estimate (SCORE), which accounts for all ET operations and tracks the first and second moments of decoder reconstructed transform coefficients. The overall framework enables optimization of ET-SVC systems for transmission over lossy networks, while accounting for all relevant conditions including the effects of quantization, channel loss, concealment, and error propagation. It thus resolves longstanding difficulties in combining truly optimal prediction and concealment with optimal endto- end distortion and error-resilient SVC coding decisions. Experiments demonstrate that the proposed scheme offers substantial performance gains over existing error-resilient SVC systems, under a wide range of packet loss and bit rates.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !