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  2. 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.

  3. Resolution (logic) - Wikipedia

    en.wikipedia.org/wiki/Resolution_(logic)

    The resolution rule, as defined by Robinson, also incorporated factoring, which unifies two literals in the same clause, before or during the application of resolution as defined above. The resulting inference rule is refutation-complete, [ 6 ] in that a set of clauses is unsatisfiable if and only if there exists a derivation of the empty ...

  4. Image restoration by artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Image_restoration_by...

    Image restoration can be broadly categorized into two main types: spatial domain and frequency domain methods. Spatial domain techniques operate directly on the image pixels, while frequency domain methods transform the image into the frequency domain using techniques such as the Fourier transform, where restoration operations are performed.

  5. 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.

  6. Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Contrastive_Language-Image...

    If the input image does not have the same resolution as the native resolution (224x224 for all except ViT-L/14@336px, which has 336x336 resolution), then the input image is scaled down by bicubic interpolation, so that its shorter side is the same as the native resolution, then the central square of the image is cropped out.

  7. Super-resolution imaging - Wikipedia

    en.wikipedia.org/wiki/Super-resolution_imaging

    These methods use other parts of the low resolution images, or other unrelated images, to guess what the high-resolution image should look like. Algorithms can also be divided by their domain: frequency or space domain. Originally, super-resolution methods worked well only on grayscale images, [18] but researchers have found methods to adapt ...

  8. CHIRP (algorithm) - Wikipedia

    en.wikipedia.org/wiki/CHIRP_(algorithm)

    CHIRP (Continuous High-resolution Image Reconstruction using Patch priors) is a Bayesian algorithm used to perform a deconvolution on images created in radio astronomy. The acronym was coined by lead author Katherine L. Bouman in 2016.

  9. Deep Learning Anti-Aliasing - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_anti-aliasing

    Deep Learning Anti-Aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. [1] DLAA depends on and requires Tensor Cores available in Nvidia RTX cards. [1]DLAA is similar to Deep Learning Super Sampling (DLSS) in its anti-aliasing method, [2] with one important differentiation being that the goal of DLSS is to increase performance at the cost of image quality, [3] whereas the ...

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