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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. Deep learning super sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    The second stage is an image upscaling step which uses the single raw, low-resolution frame to upscale the image to the desired output resolution. Using just a single frame for upscaling means the neural network itself must generate a large amount of new information to produce the high resolution output, this can result in slight hallucinations ...

  4. waifu2x - Wikipedia

    en.wikipedia.org/wiki/Waifu2x

    waifu2x is an image scaling and noise reduction program for anime-style art and other types of photos. [1] waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN). [2] [3] It uses Nvidia CUDA for computing, [4] although alternative implementations that allow for OpenCL [5] and Vulkan [6] have been created.

  5. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    An image scaled with nearest-neighbor scaling (left) and 2×SaI scaling (right) In computer graphics and digital imaging, image scaling refers to the resizing of a digital image. In video technology, the magnification of digital material is known as upscaling or resolution enhancement.

  6. Let's Enhance - Wikipedia

    en.wikipedia.org/wiki/Let's_Enhance

    Let's Enhance [1] is a Ukrainian start-up [2] which develops an online service driven by artificial intelligence which allows improving images and zooming them without losing quality. [3] According to the developers, [4] they used the super-resolution technology of machine learning. The neural network, trained on a large base of real ...

  7. 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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