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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.
Super-resolution imaging (SR) is a class of techniques that improve the resolution of an imaging system. In optical SR the diffraction limit of systems is transcended, while in geometrical SR the resolution of digital imaging sensors is enhanced.
The cross-cumulant approach facilitates the generation of virtual pixels depending on the order of the cumulant as previously mentioned. These virtual pixels can be calculated in a particular pattern from the original pixels for a 4th-order cross-cumulant image, as it is depicted in the lower image, part A.
The feature was first unveiled during CES 2023 as RTX Video Super Resolution. [3] The feature uses the on-board Tensor Cores to upscale browser video content in real time. [4] The feature is currently only available on RTX 30 and 40 series gpus with support for 20 series gpus coming in the future. [5]
Then the resolution-independent version is rendered as a raster image at the desired resolution. This technique is used by Adobe Illustrator Live Trace, Inkscape, and several recent papers. [6] Scalable Vector Graphics are well suited to simple geometric images, while photographs do not fare well with vectorization due to their complexity.
The second stage is an image upscaling step which uses the single raw, low-resolution frame to upscale the image to the desired output resolution. Using just a single frame for upscaling means the neural network itself must generate a large amount of new information to produce the high resolution output, this can result in slight hallucinations ...
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