论文标题
一种图像深度学习方法来恢复损坏的遥感产品
A single image deep learning approach to restoration of corrupted remote sensing products
论文作者
论文摘要
遥感图像用于各种分析，从农业监测到救灾，再到资源计划等。这些图像可能由于多种原因而损坏，包括仪器错误和云等自然障碍。我们在这里提出了一种新的方法，用于在这种情况下仅使用损坏的图像作为输入来重建缺失信息。深度图像先验方法消除了对预训练网络或图像数据库的需求。结果表明，该方法很容易击败传统单像方法的性能。
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.
