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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.
Images can often be improved – or even transformed – by using graphics software such as Photoshop or the free GIMP and Paint.NET applications. Many other programs also have photo-enhancing tools, including facilities for semi-automatic image enhancement, so that you need only click a button, or choose a thumbnail, to have a positive effect on image quality.
Image editing encompasses the processes of altering images, whether they are digital photographs, traditional photo-chemical photographs, or illustrations. Traditional analog image editing is known as photo retouching, using tools such as an airbrush to modify photographs or edit illustrations with any traditional art medium.
Let's Enhance [1] is a Ukrainian start-up [2] which develops an online service driven by artificial intelligence which allows improving images and zooming them without losing quality. [3] According to the developers, [4] they used the super-resolution technology of machine learning. The neural network, trained on a large base of real ...
Photo Editor: Enhance and balance color, resize, add effects, Overlays and clip-arts. Photo Batch-Editor: Process multiple photos at once, rename multiple photos at once. Collage Creator: joins multiple photos into poster-like single page or into one final photo. GIF Animation: Make multiple images into GIF-animated image.
For image processing, deconvolution is the process of approximately inverting the process that caused an image to be blurred. Specifically, unsharp masking is a simple linear image operation—a convolution by a kernel that is the Dirac delta minus a gaussian blur kernel.
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