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Machine learning-enabled UAV hyperspectral identification of tomato spotted wilt virus in tobacco. [PDF]
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Chlorophyll content retrieval from hyperspectral remote sensing imagery
Environmental Monitoring and Assessment, 2015Chlorophyll content is the essential parameter in the photosynthetic process determining leaf spectral variation in visible bands. Therefore, the accurate estimation of the forest canopy chlorophyll content is a significant foundation in assessing forest growth and stress affected by diseases.
Xiguang, Yang, Ying, Yu, Wenyi, Fan
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M2H-Net: A Reconstruction Method For Hyperspectral Remotely Sensed Imagery
ISPRS Journal of Photogrammetry and Remote Sensing, 2021Abstract Hyperspectral remote sensing can get spatially and spectrally continuous data simultaneously. However, the imaging equipment is usually expensive and complex, along with the low spatial resolution. In recent years, reconstruction of hyperspectral image by deep learning from the widely used low-cost, high spatial resolution RGB camera, has ...
Lei Deng +6 more
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An Efficient Classifier Design for Remote Sensing Hyperspectral Imagery
2015 7th International Conference on Recent Advances in Space Technologies (RAST), 2015Among the various classifiers, the Support Vector Data Description (SVDD) is a well-known strong classifier since it uses nonparametric boundary approach that constructs the minimum hypersphere enclosing the target objects as much as possible. The SVDD has been used in many studies for classification, anomaly and target detection problems on airborne ...
Binol, Hamidullah, BAL, Abdullah
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Underwater target detection with hyperspectral remote-sensing imagery
2010 IEEE International Geoscience and Remote Sensing Symposium, 2010This paper presents a new way of detecting underwater targets with hyperspectral remote-sensing data. The idea is to use a bathymetric model of subsurface reflectance to correct the spectral distortions due to water crossing. Then we derive the Matched filter (MF) from the Likelihood Ratio Test (LRT) built to decide whether the target is present or ...
Sylvain Jay, Mireille Guillaume
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Dehazing method for hyperspectral remote sensing imagery with hyperspectral linear unmixing
SPIE Proceedings, 2016Haze always exists in hyper-spectral remote sensing imagery, and it is a key reason that influences the effective information extraction of hyper-spectral images. Specially, when the faint haze covers part of the target in remote sensing images, the target still can be detected but not clear.
Yuquan Gan +3 more
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Superpixel-Guided Sparse Unmixing for Remotely Sensed Hyperspectral Imagery
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019Sparse representation-based approaches have been successfully applied to remotely sensed hyperspectral image unmixing. In recent years, sparse unmixing techniques have incorporated spatial information into the sparse unmixing model, achieving improved fractional abundance results.
Shaoquan Zhang +6 more
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Feature-Driven Multilayer Visualization for Remotely Sensed Hyperspectral Imagery
IEEE Transactions on Geoscience and Remote Sensing, 2010Displaying the abundant information contained in a remotely sensed hyperspectral image is a challenging problem. Currently, no approach can satisfactorily render the desired information at arbitrary levels of detail. In this paper, we present a feature-driven multilayer visualization technique that automatically chooses data visualization techniques ...
Shangshu Cai +2 more
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