Results 1 to 10 of about 18,058 (162)
IEEE Access, 2023 Since hyperspectral remote sensing images are three-dimensional data cubes with spatial and spectral information, with many wavebands and high inter-band correlation, the number of training samples required for classification is greatly increased.
Chaozhu Zhang +3 more
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IET Image Processing, 2022 Although hyperspectral data, especially spaceborne images, are rich in spectral information, their spatial resolution is usually low due to the limitation of sensor design and other factors.
Haoyang Yu +5 more
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Research and Application of Several Key Techniques in Hyperspectral Image Preprocessing
Frontiers in Plant Science, 2021 This paper focuses on image segmentation, image correction and spatial-spectral dimensional denoising of images in hyperspectral image preprocessing to improve the classification accuracy of hyperspectral images.
Yu-hang Li +15 more
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Remote Sensing, 2023 Hyperspectral images (HSI) have high-dimensional and complex spectral characteristics, with dozens or even hundreds of bands covering the same area of pixels.
Lijing Bu +4 more
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DEEP NO LEARNING APPROACH FOR UNSUPERVISED CHANGE DETECTION IN HYPERSPECTRAL IMAGES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 Unsupervised deep transfer-learning based change detection (CD) methods require pre-trained feature extractor that can be used to extract semantic features from the target bi-temporal scene.
S. Saha +4 more
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Hyperspectral and Multispectral Image Fusion by Deep Neural Network in a Self-Supervised Manner
Remote Sensing, 2021 Compared with multispectral sensors, hyperspectral sensors obtain images with high- spectral resolution at the cost of spatial resolution, which constrains the further and precise application of hyperspectral images.
Jianhao Gao, Jie Li, Menghui Jiang
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SICE Journal of Control, Measurement, and System Integration, 2022 Recently, the utilization of hyperspectral images containing several hundred wavelength information has been increasing in various fields. If a hyperspectral image can be estimated from a low-cost RGB image that has only R, G, and B wavelength ...
Ryoji Sato +3 more
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Deep Learning in Medical Hyperspectral Images: A Review
Sensors, 2022 With the continuous progress of development, deep learning has made good progress in the analysis and recognition of images, which has also triggered some researchers to explore the area of combining deep learning with hyperspectral medical images and ...
Rong Cui +6 more
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Agricultural plant hyperspectral imaging dataset
Компьютерная оптика, 2023 Detailed automated analysis of crop images is critical to the development of smart agriculture and can significantly improve the quantity and quality of agricultural products.
A.V. Gaidel +6 more
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FUSION OF HYPERSPECTRAL AND PANCHROMATIC IMAGES USING SPECTRAL UNMIXING RESULTS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 Hyperspectral imaging, due to providing high spectral resolution images, is one of the most important tools in the remote sensing field. Because of technological restrictions hyperspectral sensors has a limited spatial resolution.
R. Rajabi, H. Ghassemian
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