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  2. Image restoration by artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Image_restoration_by...

    Image restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image. Corruption may come in many forms such as motion blur , noise and camera mis-focus. [ 1 ]

  3. Luminar Neo - Wikipedia

    en.wikipedia.org/wiki/Luminar_Neo

    Upscale AI helps upscale a photo up to 600% and enhances image resolution in a natural way. Background Removal AI automatically removes the background behind one or multiple subjects in a photo. HDR Merge lets users combine up to 10 photos to create an HDR image that brings out important details from the brightest and darkest parts of photos.

  4. 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 ...

  5. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.

  6. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    Image editors may feature a number of algorithms which can add or remove noise in an image. Some JPEG artifacts can be removed; dust and scratches can be removed and an image can be de-speckled. Noise reduction merely estimates the state of the scene without the noise and is not a substitute for obtaining a "cleaner" image.

  7. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    The difference between a small and large Gaussian blur. In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and reduce detail.