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  2. 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.

  3. Comparison gallery of image scaling algorithms - Wikipedia

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

    Examples of algorithms for this task include New Edge-Directed Interpolation (NEDI), [1] [2] Edge-Guided Image Interpolation (EGGI), [3] Iterative Curvature-Based Interpolation (ICBI), [citation needed] and Directional Cubic Convolution Interpolation (DCCI). [4] A study found that DCCI had the best scores in PSNR and SSIM on a series of test ...

  4. Deep learning super sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    The first iteration of DLSS is a predominantly spatial image upscaler with two stages, both relying on convolutional auto-encoder neural networks. [21] The first step is an image enhancement network which uses the current frame and motion vectors to perform edge enhancement, and spatial anti-aliasing. The second stage is an image upscaling step ...

  5. hqx - Wikipedia

    en.wikipedia.org/wiki/Hqx

    hqx ("high quality scale") is a set of 3 image upscaling algorithms developed by Maxim Stepin. The algorithms are hq2x , hq3x , and hq4x , which magnify by a factor of 2, 3, and 4 respectively. It was initially created in 2003 for the Super NES emulator ZSNES , [ 1 ] and is used in emulators such as Nestopia , F. CEUX Snes9x., and Snes9x .

  6. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric transformations with no loss of image quality. When scaling a raster graphics image, a new image with a higher or lower number of pixels must be generated. In the case of decreasing the pixel number (scaling down), this usually ...

  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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