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The future of image restoration is likely to be driven by developments in deep learning and artificial intelligence. Convolutional neural networks (CNNs) have shown promising results in various image restoration tasks, including denoising, super-resolution, and inpainting.
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Digital photograph restoration uses image editing techniques to remove undesired visible features, such as dirt, scratches, or signs of aging. People use raster graphics editors to repair digital images, or to add or replace torn or missing pieces of the physical photograph.
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