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Supersampling or supersampling anti-aliasing (SSAA) is a spatial anti-aliasing method, i.e. a method used to remove aliasing (jagged and pixelated edges, colloquially known as "jaggies") from images rendered in computer games or other computer programs that generate imagery. Aliasing occurs because unlike real-world objects, which have ...
Compared to supersampling, multisample anti-aliasing can provide similar quality at higher performance, or better quality for the same performance. Further improved results can be achieved by using rotated grid subpixel masks. The additional bandwidth required by multi-sampling is reasonably low if Z and colour compression are available. [8]
The neural networks are trained on a per-game basis by generating a "perfect frame" using traditional supersampling to 64 samples per pixel, as well as the motion vectors for each frame. The data collected must be as comprehensive as possible, including as many levels, times of day, graphical settings, resolutions, etc. as possible.
The input data is the rendered image and optionally the luminance data. [3]Acquire the luminance data. [3] This data could be passed into the FXAA algorithm from the rendering step as an alpha channel embedded into the image to be antialiased, calculated from the rendered image, or approximated by using the green channel as the luminance data.
In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate.Theoretically, a bandwidth-limited signal can be perfectly reconstructed if sampled at the Nyquist rate or above it.
Pixels sampled in past frames are blended with pixels sampled in the current frame to produce an anti-aliased image. Although this method makes TAA achieve a result comparable to supersampling, the technique inevitably causes ghosting and blurriness to the image. [1]
Widely used chroma subsampling formats. Chroma subsampling is the practice of encoding images by implementing less resolution for chroma information than for luma information, taking advantage of the human visual system's lower acuity for color differences than for luminance.
It produces far fewer artifacts than nearest-neighbor rotation algorithms, and like EPX, it does not introduce new colors into the image (unlike most interpolation systems). [ 21 ] The algorithm first scales the image to 8 times its original size with a modified Scale2× algorithm which treats similar (rather than identical) pixels as matches.