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Abstract

A method for processing images comprising: capturing a plurality of degraded images of a first real-world environment with a first sensor; processing each degraded image with a first, untrained convolutional neural network, via a Deep Image Prior approach, to obtain a plurality of clean images, wherein each clean image corresponds to a degraded image; pairing each clean image with its corresponding degraded image to create a plurality of degraded/clean image pairs; training, via a supervised learning approach, a machine learning model to learn a function for converting degraded images into restored images based on the plurality of degraded/clean image pairs; capturing a second plurality of degraded images of a second real-world environment; and using the trained machine learning model to convert the second plurality of degraded images into restored images based on the learned function.

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First Claim