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2. Image restoration by artificial intelligence - Wikipedia

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

   Corruption may come in many forms such as motion blur, noise and camera mis-focus. [1] Image restoration is performed by reversing the process that blurred the image and such is performed by imaging a point source and use the point source image, which is called the Point Spread Function (PSF) to restore the image information lost to the ...

3. Deep image prior - Wikipedia

   en.wikipedia.org/wiki/Deep_Image_Prior

   Deep image prior is a type of convolutional neural network used to enhance a given image with no prior training data other than the image itself. A neural network is randomly initialized and used as prior to solve inverse problems such as noise reduction, super-resolution, and inpainting.

4. Comparison of image viewers - Wikipedia

   en.wikipedia.org/wiki/Comparison_of_image_viewers

   Resize, crop, rotate, flip, JPEG lossless rotate/flip/crop, adjust exposure and colors etc., filters (sharpen, blur, average, emboss), batch convert, batch rename, edit IPTC info Free for non-commercial use Xv: View as ASCII or hex, magnify, determine pixel values

5. 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 ...

6. 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.

7. Spatial anti-aliasing - Wikipedia

   en.wikipedia.org/wiki/Spatial_anti-aliasing

   However, while useful for photo-like images, a simple anti-aliasing approach (such as super-sampling and then averaging) may actually worsen the appearance of some types of line art or diagrams (making the image appear fuzzy), especially where most lines are horizontal or vertical.