Remote sensing image cloud removal by deep image prior with a multitemporal constraint

Abstract

The existence of clouds largely goes against the monitoring of Earth from remote sensing satellites, and how to remove these clouds is of vital importance. To address the issue, we propose a generative method with two main aspects: 1) we introduce deep image prior as the generator to reconstruct the missing information covered by clouds; 2) to ensure the spatial information of reconstruction results, we attempt to make use of optical images from other periods as the constraint. The paper presents both simulation and real data experiments conducted with Landsat-8 and Sentinel-2 data. The experimental results indicate that the proposed method outperforms the traditional cloud removal methods in both qualitative and quantitative evaluation results.