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Video super-resolution (VSR) is the process of generating high-resolution video frames from the given low-resolution video frames. Unlike single-image super-resolution (SISR) , the main goal is not only to restore more fine details while saving coarse ones, but also to preserve motion consistency.
Nvidia has also introduced Deep learning dynamic super resolution (DLDSR), a related and opposite technology where the graphics are rendered at a higher resolution, then downsampled to the native display resolution using an artificial intelligence-assisted downsampling algorithm to achieve higher image quality than rendering at native resolution.
Let's Enhance [1] is a Ukrainian start-up [2] which develops an online service driven by artificial intelligence which allows improving images and zooming them without losing quality. [3] According to the developers, [4] they used the super-resolution technology of machine learning. The neural network, trained on a large base of real ...
In video technology, the magnification of digital material is known as upscaling or resolution enhancement. When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric transformations with no loss of image quality .
H.264 can often perform radically better than MPEG-2 video—typically obtaining the same quality at half of the bit rate or less, especially on high bit rate and high resolution video content. [49] Like other ISO/IEC MPEG video standards, H.264/AVC has a reference software implementation that can be freely downloaded. [50]
The quality the codec can achieve is heavily based on the compression format the codec uses. A codec is not a format, and there may be multiple codecs that implement the same compression specification – for example, MPEG-1 codecs typically do not achieve quality/size ratio comparable to codecs that implement the more modern H.264 specification.
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