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2. 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 ...

3. AOL Mail

   mail.aol.com

   Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

4. Photopea - Wikipedia

   en.wikipedia.org/wiki/Photopea

   Photopea (/ ˈ f oʊ t ə ˈ p iː / FOH-tə-PEE) is a web-based photo and graphics editor. It is used for image editing, making illustrations, web design or converting between different image formats. Photopea is advertising-supported software.

5. Comparison of image viewers - Wikipedia

   en.wikipedia.org/wiki/Comparison_of_image_viewers

   Non-destructive editor, Auto Enhance Images, Duplicate, Upload, Favorite STDU Viewer: No No No No Yes No No Yes Windows Photo Viewer: No No Yes: Exif Yes rotate, lossless JPEG rotate, annotate TIFF images Yes Yes rotate only Yes XnView and XnViewMP Yes name, date, file size, image size, meta data, ... Yes individual, linear Yes IPTC, Exif, JPEG ...

6. Unsharp masking - Wikipedia

   en.wikipedia.org/wiki/Unsharp_masking

   If the difference is greater than a user-specified threshold setting, the images are (in effect) subtracted. Digital unsharp masking is a flexible and powerful way to increase sharpness, especially in scanned images. Unfortunately, it may create unwanted conspicuous edge effects or increase image noise.

7. Image registration - Wikipedia

   en.wikipedia.org/wiki/Image_registration

   Manual methods provide tools to align the images manually. Interactive methods reduce user bias by performing certain key operations automatically while still relying on the user to guide the registration. Semi-automatic methods perform more of the registration steps automatically but depend on the user to verify the correctness of a registration.