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  2. Let's Enhance - Wikipedia

    en.wikipedia.org/wiki/Let's_Enhance

    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 ...

  3. Wikipedia:How to improve image quality - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:How_to_improve...

    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.

  4. Fotor - Wikipedia

    en.wikipedia.org/wiki/Fotor

    Fotor is a multi-platform photo editing software. [3] It was first launched in 2012 and was dubbed "Photoshop Lite" by the BBC. [4] Fotor's software is available on mobile devices, desktop computers, and online as a web app. [5] It offers a suite of image editing tools and features for users to edit and enhance photos quickly and easily.

  5. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    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.

  6. 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. In a ...

  7. Deep image prior - Wikipedia

    en.wikipedia.org/wiki/Deep_Image_Prior

    Deep image prior is a type of convolutional neural network used to enhance a given image with no prior training data other than the image itself. A neural network is randomly initialized and used as prior to solve inverse problems such as noise reduction , super-resolution , and inpainting .

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