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Image enhancement techniques (like contrast stretching or de-blurring by a nearest neighbor procedure) provided by imaging packages use no a priori model of the process that created the image. With image enhancement noise can effectively be removed by sacrificing some resolution, but this is not acceptable in many applications.
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 first iteration of DLSS is a predominantly spatial image upscaler with two stages, both relying on convolutional auto-encoder neural networks. [23] 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 ...
The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.
Fotor One-Tap Photo Enhancer is a tool that is designed to automatically improve image quality and fix common imaging problems. [6] [7] Fotor GoArt is a tool to turn photos into classical painting style artwork. [8] Fotor AI Background Remover is a tool that allows users to remove backgrounds from their images with one click. [9]
Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [85] Google Photos, [86] and the Adobe Suite (Adobe Firefly). [87] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model.
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