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Aliasing in spatially sampled signals (e.g., moiré patterns in digital images) is referred to as spatial aliasing. Aliasing is generally avoided by applying low-pass filters or anti-aliasing filters (AAF) to the input signal before sampling and when converting a signal from a higher to a lower sampling rate.
In digital signal processing, spatial anti-aliasing is a technique for minimizing the distortion artifacts when representing a high-resolution image at a lower resolution. Anti-aliasing is used in digital photography , computer graphics , digital audio , and many other applications.
The effect of jaggies can be reduced by a graphics technique known as spatial anti-aliasing. Anti-aliasing smooths out jagged lines by surrounding them with transparent pixels to simulate the appearance of fractionally-filled pixels when viewed at a distance. The downside of anti-aliasing is that it reduces contrast – rather than sharp black ...
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 ...
Temporal anti-aliasing (TAA) is a spatial anti-aliasing technique for computer-generated video that combines information from past frames and the current frame to remove jaggies in the current frame. In TAA, each pixel is sampled once per frame but in each frame the sample is at a different location within the frame.
Deep learning anti-aliasing (DLAA), a type of spatial and temporal anti-aliasing method relying on dedicated tensor core processors Deep learning super sampling (DLSS), a family of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are available in a number of video games.
An anti-aliasing filter (AAF) is a filter used before a signal sampler to restrict the bandwidth of a signal to satisfy the Nyquist–Shannon sampling theorem over the band of interest. Since the theorem states that unambiguous reconstruction of the signal from its samples is possible when the power of frequencies above the Nyquist frequency is ...
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