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
FDT-Net: Deep-Learning Network for Thin-Cloud Removal in Remote Sensing Image Using Frequency-Domain Training Strategy
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2024.3389995
Abstract: Earth’s surface is covered by thin clouds throughout the year, which greatly limits the application of remote sensing (RS) images obtained at a high cost. Currently, deep-learning technology has received widespread attention in the field… read more here.
Keywords: deep learning; image; fdt net; thin cloud ... See more keywords
PM-LSMN: A Physical-Model-Based Lightweight Self-Attention Multiscale Net for Thin Cloud Removal
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2024.3403674
Abstract: Recently, deep learning-based thin cloud removal methods have led to remarkable results. However, these deep learning models often have intricate structures, numerous parameters, and entail substantial training costs, rendering them impractical for widespread implementation in… read more here.
Keywords: thin cloud; attention; cloud; cloud removal ... See more keywords
Double Rank-One Prior: Thin Cloud Removal by Visible Bands
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2024.3396874
Abstract: Thin cloud removal for multispectral (MS) or hyperspectral (HS) images is a ubiquitous and fundamental problem in remote sensing. However, it is prohibitively challenging due to the ill-posedness and underdetermination of the image formation. The… read more here.
Keywords: thin cloud; cloud; removal; cloud removal ... See more keywords
DecloudNet: Cross-Patch Consistency is a Nontrivial Problem for Thin Cloud Removal From Wide-Swath Multispectral Images
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2024.3427788
Abstract: Cloud cover leads to great loss of spatial details in wide-swath multispectral images, and thus significantly affects their application value. Wide-swath images are huge in size and are usually cropped into patches before thin cloud… read more here.
Keywords: wide swath; cross patch; thin cloud; cloud ... See more keywords
2DDSRU-MobileNet: an end-to-end cloud-noise-robust lightweight convolution neural network
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.18.024511
Abstract: Abstract. To solve the problem of thin-cloud interference of remote sensing (RS) images under hardware-constrained environments, we present an end-to-end cloud-noise-robust lightweight convolution neural network model, 2DDSRU-MobileNet, based on MobileNetV3-small. We first propose a denoised… read more here.
Keywords: end; convolution; thin cloud; cloud ... See more keywords
Two-Level Supervised Network for Small Ship Target Detection in Shallow Thin Cloud-Covered Optical Satellite Images
Sign Up to like & getrecommendations! Published in 2024 at "Applied Sciences"
DOI: 10.3390/app142411558
Abstract: Ship detection under cloudy and foggy conditions is a significant challenge in remote sensing satellite applications, as cloud cover often reduces contrast between targets and backgrounds. Additionally, ships are small and affected by noise, making… read more here.
Keywords: detection; target detection; thin cloud; ship ... See more keywords