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Interpretation of Hyperspectral Image Data
1999The data produced by the imaging spectrometers of Section 1.4.6 is different from that of multispectral instruments owing to the enormous number of wavebands recorded — leading to the term hyperspectrdl. For a given geographical area imaged, the data produced can be viewed as a cube, as shown in Fig.
John A. Richards, Xiuping Jia
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Coupled adversarial learning for fusion classification of hyperspectral and LiDAR data
Information Fusion, 2023Wei Fu
exaly
Deep Hierarchical Vision Transformer for Hyperspectral and LiDAR Data Classification
IEEE Transactions on Image Processing, 2022Zhixiang Xue, Xiong Tan, Liu Bing
exaly
Processing Techniques for Hyperspectral Data
2010The basic knowledge about the differences between multi- and hyperspectral data is provided and the potential of hyperspectral image analysis is highlighted. Relevant pre-processing steps and different ways to analyze hyperspectral data are presented. The chapter closes with a short outlook on expected developments with relevance for urban applications.
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Hyperspectral Remote Sensing Data Analysis and Future Challenges
IEEE Geoscience and Remote Sensing Magazine, 2013Antonio J Plaza +2 more
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Deep Learning for Classification of Hyperspectral Data: A Comparative Review
IEEE Geoscience and Remote Sensing Magazine, 2019Nicolas Audebert +2 more
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Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles
IEEE Transactions on Geoscience and Remote Sensing, 2008Mathieu Fauvel +2 more
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Classification of hyperspectral data from urban areas based on extended morphological profiles
IEEE Transactions on Geoscience and Remote Sensing, 2005Jon Atli Benediktsson
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Deep Learning-Based Classification of Hyperspectral Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014Yushi Chen, Yanfeng Gu
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