Content-Adaptive Motion Compensated Frequency Selective Extrapolation for Error Concealment in Video Communication

TL;DR

This paper introduces a content-adaptive, motion compensated frequency selective extrapolation algorithm for error concealment in video communication, significantly improving visual quality over existing methods.

Contribution

The proposed algorithm adaptively models video content for enhanced error concealment, outperforming previous algorithms in PSNR gains by leveraging content-specific information.

Findings

Up to 0.51 dB PSNR improvement over the baseline algorithm

More than 3 dB PSNR gain compared to other error concealment methods

Effective exploitation of remaining information in distorted sequences

Abstract

If digital video data is transmitted over unreliable channels such as the internet or wireless terminals, the risk of severe image distortion due to transmission errors is ubiquitous. To cope with this, error concealment can be applied on the distorted data at the receiver. In this contribution we propose a novel spatio-temporal error concealment algorithm, the Content-Adaptive Motion Compensated Frequency Selective Extrapolation. The algorithm operates in two stages, whereas at first the motion in a distorted sequence is estimated. After that, a model of the signal is generated for concealing the distortion. The novel algorithm is based on an already existent error concealment algorithm. But by adapting the model generation to the content of a sequence, the novel algorithm is able to exploit the remaining information, which is still available in the distorted sequence, more effectively compared to the original algorithm. In doing so, a visually noticeable gain of up to 0.51 dB PSNR compared to the underlying algorithm and more than 3 dB compared to other error concealment algorithms can be achieved.