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2. 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 ...

3. 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.

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. 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 ...

6. Template:Upscaled images - Wikipedia

   en.wikipedia.org/wiki/Template:Upscaled_images

   This tag is intended to identify articles with historical images that have been upscaled by an AI process. Template parameters [Edit template data] This template prefers inline formatting of parameters. Parameter Description Type Status Affected area 1 Text to replace the word "article", usually "section" Example section Auto value section Line optional Month and year date The month and year ...

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 ...