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2. Image restoration by artificial intelligence - Wikipedia

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

   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.

3. Comparison gallery of image scaling algorithms - Wikipedia

   en.wikipedia.org/wiki/Comparison_gallery_of...

   Then the resolution-independent version is rendered as a raster image at the desired resolution. This technique is used by Adobe Illustrator Live Trace, Inkscape, and several recent papers. [6] Scalable Vector Graphics are well suited to simple geometric images, while photographs do not fare well with vectorization due to their complexity.

4. Deep learning super sampling - Wikipedia

   en.wikipedia.org/wiki/Deep_learning_super_sampling

   Nvidia has also introduced Deep learning dynamic super resolution (DLDSR), a related and opposite technology where the graphics are rendered at a higher resolution, then downsampled to the native display resolution using an artificial intelligence-assisted downsampling algorithm to achieve higher image quality than rendering at native resolution.

5. Google DeepMind’s new Veo 2 AI video generator trounces ...

   www.aol.com/finance/google-deepmind-veo-2-ai...

   Just seven months after it unveiled its Veo AI video generator, Alphabet division Google DeepMind has announced Veo 2. The new tool can generate videos of up to 4K resolution, whereas the first ...

6. Super-resolution imaging - Wikipedia

   en.wikipedia.org/wiki/Super-resolution_imaging

   There are many both single-frame and multiple-frame variants of SR. Multiple-frame SR uses the sub-pixel shifts between multiple low resolution images of the same scene. It creates an improved resolution image fusing information from all low resolution images, and the created higher resolution images are better descriptions of the scene.

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 ...