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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. 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.

  4. 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.

  5. Fast approximate anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Fast_approximate_anti-aliasing

    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.

  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. Comparison gallery of image scaling algorithms - Wikipedia

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

    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.

  8. Deep Learning Super Sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    Nvidia advertised DLSS as a key feature of the GeForce 20 series cards when they launched in September 2018. [5] At that time, the results were limited to a few video games, namely Battlefield V, [6] or Metro Exodus, because the algorithm had to be trained specifically on each game on which it was applied and the results were usually not as good as simple resolution upscaling.

  9. Oversampling - Wikipedia

    en.wikipedia.org/wiki/Oversampling

    This averaging is only effective if the signal contains sufficient uncorrelated noise to be recorded by the ADC. [3] If not, in the case of a stationary input signal, all 2 n {\displaystyle 2^{n}} samples would have the same value and the resulting average would be identical to this value; so in this case, oversampling would have made no ...