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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.
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 ...
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 editors can change the pixels to enhance the image in many ways. The pixels can be changed as a group or individually by the sophisticated algorithms within the image editors. This article mostly refers to bitmap graphics editors, which are often used to alter photographs and other raster graphics.
Unwanted color casts are removed and the image's contrast or sharpening may be altered to restore the contrast range or detail believed to have been in the original physical image. Digital image processing techniques included in image enhancement and image restoration software are also applied to digital photograph restoration.
Image quality assessment is part of the quality of experience measures. Image quality can be assessed using two methods: subjective and objective. Subjective methods are based on the perceptual assessment of a human viewer about the attributes of an image or set of images, while objective methods are based on computational models that can ...
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