DOI: 10.48550/arxiv.2105.06533
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Abstract: Applications in materials and biological imaging are limited by the ability to collect high-resolution data over large areas in practical amounts of time. One possible solution to this problem is to collect low-resolution data and interpolate to produce a high-resolution image. However, state-of-the-art super-resolution algorithms are typically designed for natural images, require aligned pairing of high and low-resolution training data for optimal performance, and do not directly incorporate a model of the im… Show more

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