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Spatiotemporal Image Fusion in Remote Sensing [PDF]
Remote Sensing, 2019 In this paper, we discuss spatiotemporal data fusion methods in remote sensing. These methods fuse temporally sparse fine-resolution images with temporally dense coarse-resolution images. This review reveals that existing spatiotemporal data fusion methods are mainly dedicated to blending optical images. There is a limited number of studies focusing on
Mariana Belgiu, Alfred Stein
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An Uncertainty Descriptor for Quantitative Measurement of the Uncertainty of Remote Sensing Images
Remote Sensing, 2019 Reliable image classification results are crucial for the application of remote sensing images, but the reliability of image classification has received less attention. In particular, the inherent uncertainty of remote sensing images has been disregarded.
Qi Zhang, Penglin Zhang
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Water body extraction from remote sensing images is an important task. Deep learning has become a more popular method for extracting water bodies from remote sensing images.
Mengya Li +5 more
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, 2020 The detection performance of small objects in remote sensing images is not satisfactory compared to large objects, especially in low-resolution and noisy images.
Chao, Dennis +4 more
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Neural Radiance Fields for High-Resolution Remote Sensing Novel View Synthesis
Remote Sensing, 2023 Remote sensing images play a crucial role in remote sensing target detection and 3D remote sensing modeling, and the enhancement of resolution holds significant application implications.
Junwei Lv +4 more
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A partially unsupervised cascade classifier for the analysis of multitemporal remote-sensing images [PDF]
, 2002 A partially unsupervised approach to the classification of multitemporal remote-sensing images is presented. Such an approach allows the automatic classification of a remote-sensing image for which training data are not available, drawing on the ...
Bruzzone, Lorenzo +1 more
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Target Detection Method for Low-Resolution Remote Sensing Image Based on ESRGAN and ReDet
Photonics, 2021 With the widespread use of remote sensing images, low-resolution target detection in remote sensing images has become a hot research topic in the field of computer vision.
Yuwu Wang, Guobing Sun, Shengwei Guo
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Compressive Hyperspectral Imaging Using Progressive Total Variation [PDF]
, 2014 Compressed Sensing (CS) is suitable for remote acquisition of hyperspectral images for earth observation, since it could exploit the strong spatial and spectral correlations, llowing to simplify the architecture of the onboard sensors. Solutions proposed
Barducci, Alessandro +4 more
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IEEE Access, 2020 Road edge detection from remote sensing images, as an important ground object type, plays an important role in people’s life and travel and urban planning and development, and extracting road information from remote sensing images has practical ...
Chen Guobin, Zengwu Sun, Li Zhang
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Remote sensing image fusion via compressive sensing [PDF]
ISPRS Journal of Photogrammetry and Remote Sensing, 2019 Abstract In this paper, we propose a compressive sensing-based method to pan-sharpen the low-resolution multispectral (LRM) data, with the help of high-resolution panchromatic (HRP) data. In order to successfully implement the compressive sensing theory in pan-sharpening, two requirements should be satisfied: (i) forming a comprehensive dictionary in
Morteza Ghahremani +3 more
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