Image Restoration for Remote Sensing: Overview and toolbox
Behnood Rasti, Yi Chang, Emanuele Dalsasso, Laurent Denis, Pedram Ghamisi · IEEE Geoscience and Remote Sensing Magazine · 2021
Remote sensing provides valuable information about objects and areas from a distance in either active (e.g., radar and lidar) or passive (e.g., multispectral and hyperspectral) modes. The quality of data acquired by remotely sensed imaging sensors (active and passive) is often degraded by a variety of noise types and artifacts. Image restoration, which is a vibrant field of research in the remote sensing community, is the task of recovering a true unknown image from a degraded observed one. Each imaging sensor induces unique noise types and artifacts into the observed image. This fact has led to the expansion of restoration techniques along different paths according to sensor type.