UnCRtainTS: Uncertainty Quantification for Cloud Removal in Optical Satellite Time Series

04/11/2023
by   Patrick Ebel, et al.
0

Clouds and haze often occlude optical satellite images, hindering continuous, dense monitoring of the Earth's surface. Although modern deep learning methods can implicitly learn to ignore such occlusions, explicit cloud removal as pre-processing enables manual interpretation and allows training models when only few annotations are available. Cloud removal is challenging due to the wide range of occlusion scenarios – from scenes partially visible through haze, to completely opaque cloud coverage. Furthermore, integrating reconstructed images in downstream applications would greatly benefit from trustworthy quality assessment. In this paper, we introduce UnCRtainTS, a method for multi-temporal cloud removal combining a novel attention-based architecture, and a formulation for multivariate uncertainty prediction. These two components combined set a new state-of-the-art performance in terms of image reconstruction on two public cloud removal datasets. Additionally, we show how the well-calibrated predicted uncertainties enable a precise control of the reconstruction quality.

READ FULL TEXT

page 1

page 3

page 8

research
12/14/2019

Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks

Satellite images hold great promise for continuous environmental monitor...
research
01/24/2022

SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud Removal

About half of all optical observations collected via spaceborne satellit...
research
12/23/2021

Cloud Removal from Satellite Images

In this report, we have analyzed available cloud detection technique usi...
research
08/08/2023

DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite Images

Optical satellite images are a critical data source; however, cloud cove...
research
12/21/2022

MM811 Project Report: Cloud Detection and Removal in Satellite Images

For satellite images, the presence of clouds presents a problem as cloud...
research
09/16/2020

Multi-Sensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery

This work has been accepted by IEEE TGRS for publication. The majority o...
research
04/19/2019

Assessing the Sharpness of Satellite Images: Study of the PlanetScope Constellation

New micro-satellite constellations enable unprecedented systematic monit...

Please sign up or login with your details

Forgot password? Click here to reset