Data fusion of satellite imagery for generation of daily cloud free images at high resolution level
Natalya Ivanchuk (1), Peter Kogut (2), Petro Martyniuk (1) ((1), National University of Water, Environmental Engineering Ukraine, (2) Oles, Honchar Dnipro National University Ukraine)

TL;DR
This paper introduces a variational data fusion method to generate high-resolution, daily cloud-free satellite images by combining multi-spectral data from Sentinel-2 and MODIS, addressing cloud contamination issues.
Contribution
The paper presents a novel variational approach for fusing multi-resolution satellite images from different sensors to produce cloud-free, high-resolution daily images.
Findings
Effective removal of clouds from Sentinel-2 images
High-resolution daily cloud-free image generation
Improved data quality for satellite imagery analysis
Abstract
In this paper we discuss a new variational approach to the Date Fusion problem of multi-spectral satellite images from Sentinel-2 and MODIS that have been captured at different resolution level and, arguably, on different days. The crucial point of our approach that the MODIS image is cloud-free whereas the images from Sentinel-2 can be corrupted by clouds or noise.
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Taxonomy
TopicsAdvanced Image Fusion Techniques · Remote-Sensing Image Classification · Infrared Target Detection Methodologies
