The AV1 codec added a new in-loop super-resolution mode that allows a frame to be encoded at a lower resolution, and then super-resolved normatively to the full resolution, before updating the reference buffers. While encoding at lower resolution and super-resolving to a higher resolution is not a new concept, this is the first time such a mode has been normatively incorporated in a standardized video codec. To this end, AV1 has not only added support for across-scale motion prediction to allow predicting a lower resolution version of a frame from higher resolution reference buffers, but also made various simplifications to the super-resolving process itself after reconstruction to make it both software and hardware-friendly in implementation. Specifically, the super-resolving process in AV1 comprises of normative linear upscaling, followed by a restoration operation to recover the high frequencies using another AV1 tool called loop-restoration that includes a Wiener or Self-guided filter selected in a block switchable manner. Further, in order to enable a cost-effective hardware solution with limited line-buffers, this mode only allows the upscaling/downscaling operation to be horizontal.
In this paper, we provide the details of the super-resolution mode in AV1 and some results showcasing the benefits of the same.
Google started the WebM Project in 2010 to develop open source, royalty- free video codecs designed specifically for media on the Web. The second generation codec released by the WebM project, VP9, is currently served by YouTube, and enjoys billions of views per day. Realizing the need for even greater compression efficiency to cope with the growing demand for video on the web, the WebM team embarked on an ambitious project to develop a next edition codec AV1, in a consortium of major tech companies called the Alliance for Open Media, that achieves at least a generational improvement in coding efficiency over VP9. In this paper, we focus primarily on new tools in AV1 that improve the prediction of pixel blocks before transforms, quantization and entropy coding are invoked. Specifically, we describe tools and coding modes that improve intra, inter and combined inter-intra prediction. Results are presented on standard test sets.
KEYWORDS: Video compression, Video, Video coding, Chromium, Computer programming, High dynamic range imaging, Lithium, Mobile devices, Digital image processing, Current controlled current source
Google started the WebM Project in 2010 to develop open source, royaltyfree
video codecs designed specifically for
media on the Web. The second generation codec released by the WebM project, VP9, is currently served by YouTube,
and enjoys billions of views per day. Realizing the need for even greater compression efficiency to cope with the
growing demand for video on the web, the WebM team embarked on an ambitious project to develop a next edition
codec, VP10, that achieves at least a generational improvement in coding efficiency over VP9. Starting from VP9, a set
of new experimental coding tools have already been added to VP10 to achieve decent coding gains. Subsequently,
Google joined a consortium of major tech companies called the Alliance for Open Media to jointly develop a new codec
AV1. As a result, the VP10 effort is largely expected to merge with AV1. In this paper, we focus primarily on new tools
in VP10 that improve coding of the prediction residue using transform coding techniques. Specifically, we describe tools
that increase the flexibility of available transforms, allowing the codec to handle a more diverse range or residue
structures. Results are presented on a standard test set.
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