A single image deep learning approach to restoration of corrupted remote sensing products

• URL: http://arxiv.org/abs/2004.04209v1
• Date: Wed, 8 Apr 2020 19:11:32 GMT
• Title: A single image deep learning approach to restoration of corrupted remote sensing products
• Authors: Anna Petrovskaia, Raghavendra B. Jana, Ivan V. Oseledets
• Abstract summary: The images can be corrupted due to a number of reasons, including instrument errors and natural obstacles such as clouds. We present here a novel approach for reconstruction of missing information in such cases using only the corrupted image as the input.
• Score: 15.358240034909743
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Remote sensing images are used for a variety of analyses, from agricultural monitoring, to disaster relief, to resource planning, among others. The images can be corrupted due to a number of reasons, including instrument errors and natural obstacles such as clouds. We present here a novel approach for reconstruction of missing information in such cases using only the corrupted image as the input. The Deep Image Prior methodology eliminates the need for a pre-trained network or an image database. It is shown that the approach easily beats the performance of traditional single-image methods.

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