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In this paper the potential improvements by temporal coding artifact reduction are discussed. Whereas conventional spatial methods may suffer from flicker in the processed output due to variable intra frame processing or insufficient removal of coding artifacts, the temporal strategies are capable of flicker reduction and even re-establishment of details missing in the actual input frame. In addition to several temporal filter strategies a new concept for estimating the true motion over multiple input frames is proposed. As a result an image content adaptive spatiotemporal artifact reduction system is presented yielding an even higher output quality.

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Handling input content ranging from low resolution and highly compressed internet streams up to high definition video is a challenging task for modern flat panel TVs. Considering that the consumer is accustomed to HD content, superior processing is mandatory especially for low bit-rate video with very low quality. In this paper, we describe a novel spatio-temporal and image content adaptive regularization algorithm, which can deal with this entire content well. This algorithm can significantly improve the video quality, remove spatial and temporal artifacts and even re-establish missing details. The spatio-temporal regularization combines the well-known Total Variation image model with a novel temporal constraint, being robust towards erroneous motion vectors and allowing application of block based motion estimation techniques.