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A number of companies have developed techniques to upscale video frames in real-time, such as when they are drawn on screen in a video game. Nvidia's deep learning super sampling (DLSS) uses deep learning to upsample lower-resolution images to a higher resolution for display on higher-resolution computer monitors. [9]
Scalable Vector Graphics are well suited to simple geometric images, while photographs do not fare well with vectorization due to their complexity. Note that the special characteristics of vectors allow for greater resolution example images. The other algorithms are standardized to a resolution of 160x160 and 218x80 pixels respectively.
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 ...
The available values for thumbnail size in Preferences (on the Appearance tab) are 120px, 150px, 180px, 200px, 220px (default), 250px, 300px, and 400px. As explained at Wikipedia:Extended image syntax § Size, upright=Factor will "adjust a thumbnail's size to Factor times the default thumbnail size, rounding the result to the nearest multiple of 10".
hqx ("high quality scale") is a set of 3 image upscaling algorithms developed by Maxim Stepin. The algorithms are hq2x, hq3x, and hq4x, which magnify by a factor of 2, 3, and 4 respectively.
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