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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.
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.
Images can often be improved – or even transformed – by using graphics software such as Photoshop or the free GIMP and Paint.NET applications. Many other programs also have photo-enhancing tools, including facilities for semi-automatic image enhancement, so that you need only click a button, or choose a thumbnail, to have a positive effect on image quality.
The basic concept underlying the various resolution enhancement systems is the creative use of diffraction in certain locations to offset the diffraction in others. For instance, when light diffracts around a line on the mask it will produce a series of bright and dark lines, or "bands". that will spread out the desired sharp pattern.
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 ...
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 which uses the single raw, low-resolution frame to upscale the image to the desired output resolution.
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