An assessment of thin cloud detection by applying bidirectional reflectance distribution function model‐based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Geophysical Research"
DOI: 10.1002/2017jd026707
Abstract: In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model-based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color… read more here.
Keywords: detection; reflectance; cloud; thin cloud ... See more keywords
Thin Cloud Removal Fusing Full Spectral and Spatial Features for Sentinel-2 Imagery
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3211857
Abstract: Multispectral remote sensing images are widely used for monitoring the globe. Although thin clouds can affect all optical bands, the influences of thin clouds differ with band wavelength. When processing multispectral bands at different resolutions,… read more here.
Keywords: spatial features; cloud removal; thin cloud; thin clouds ... See more keywords
Thin Cloud Removal for Remote Sensing Images Using a Physical-Model-Based CycleGAN With Unpaired Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3140033
Abstract: Thin cloud removal from remote sensing (RS) images is challenging. Recently, deep-learning-based methods have achieved excellent results using supervised training on paired image data. However, in practice, real paired image data are unavailable. Therefore, in… read more here.
Keywords: physical model; cloud removal; thin cloud; image ... See more keywords
Feedback Network for Compact Thin Cloud Removal
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3256416
Abstract: The thin cloud removal (CR) technique has great practical value for the application of remote-sensing images. Existing deep-learning-based methods have attained remarkable achievements. However, most of them neglect the inherent feature correlations in deeper layers… read more here.
Keywords: compact thin; cloud removal; crfb net; thin cloud ... See more keywords