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  2. Supersampling - Wikipedia

    en.wikipedia.org/wiki/Supersampling

    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 ...

  3. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    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.

  4. Multisample anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Multisample_anti-aliasing

    (This is not the same as supersampling but, by the OpenGL 1.5 specification, [2] the definition had been updated to include fully supersampling implementations as well.) In graphics literature in general, "multisampling" refers to any special case of supersampling where some components of the final image are not fully supersampled.

  5. Anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Anti-aliasing

    With multisample anti-aliasing (MSAA), images are computed for 4 (or 8) subpixel sample points, followed by averaging. It is slow, since the frame rate is reduced by a factor of 4 (or 8). It works well for horizontal and vertical triangle edges. For other edge angles, the gaps between subpixels can cause narrow face breakups.

  6. Spatial anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Spatial_anti-aliasing

    Near the top of an image with a receding checker-board pattern, the image is both difficult to recognise and not aesthetically appealing. In contrast, when anti-aliased the checker-board near the top blends into grey, which is usually the desired effect when the resolution is insufficient to show the detail.

  7. Deep Learning Super Sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    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.

  8. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    Image scaling can be interpreted as a form of image resampling or image reconstruction from the view of the Nyquist sampling theorem.According to the theorem, downsampling to a smaller image from a higher-resolution original can only be carried out after applying a suitable 2D anti-aliasing filter to prevent aliasing artifacts.

  9. Oversampling - Wikipedia

    en.wikipedia.org/wiki/Oversampling

    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.