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Pixlr is a group of AI-powered SaaS creative tools including Pixlr.com, Designs.ai and Vectr.com. [1] Pixlr.com is a cloud-based set of image editing tools and utilities, including AI image generation and enhancements. The Pixlr suite targets users who require simple to advanced photo editing as well as graphic design. [2]
The features include an AI image generation tool which converts text into images, as well as a background eraser to erase unwanted objects and replace the background. It also includes image filters like blur, retro, VHS, and Y2K. The apps include: Picsart Photo & Video Editor - a photo and video editing app with tools to add filters and various ...
For calculating the image containing only the background, a series of preceding images are averaged. For calculating the background image at the instant t: (,,) = = (,,) where N is the number of preceding images taken for averaging. This averaging refers to averaging corresponding pixels in the given images.
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]
CHIRP (Continuous High-resolution Image Reconstruction using Patch priors) is a Bayesian algorithm used to perform a deconvolution on images created in radio astronomy. The acronym was coined by lead author Katherine L. Bouman in 2016.
AI-based images have become more commonplace in art markets and search engines because AI-based text-to-image systems are trained from pre-existing artistic images, sometimes without the original artist's consent, allowing the software to mimic specific artists' styles.
Given an existing image, DALL-E 2 can produce "variations" of the image as individual outputs based on the original, as well as edit the image to modify or expand upon it. DALL-E 2's "inpainting" and "outpainting" use context from an image to fill in missing areas using a medium consistent with the original, following a given prompt.
Given a sufficient number of observation images, and if the set of observations vary in their phase (i.e. if the images of the scene are shifted by a sub-pixel amount), then the phase information can be used to separate the aliased high-frequency content from the true low-frequency content, and the full-resolution image can be accurately ...
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