Least Angle Regression-Based Constrained Sparse Unmixing of Hyperspectral Remote Sensing Imagery
نویسندگان
چکیده
منابع مشابه
Rolling Guidance Based Scale-Aware Spatial Sparse Unmixing for Hyperspectral Remote Sensing Imagery
Ruyi Feng 1 ID , Yanfei Zhong 2,* ID , Lizhe Wang 1,* and Wenjuan Lin 3,* 1 School of Computer Science, China University of Geosciences (Wuhan), Wuhan 430074, China; [email protected] 2 State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China 3 School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, C...
متن کاملHyperspectral Unmixing with Robust Collaborative Sparse Regression
Chang Li 1, Yong Ma 2,∗, Xiaoguang Mei 2, Chengyin Liu 1 and Jiayi Ma 2 1 School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China; [email protected] (C.L.); [email protected] (C.L.) 2 Electronic Information School, Wuhan University, Wuhan 430072, China; [email protected] (X.M.); [email protected] (J.M.) * Corresponden...
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Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. We propose to use overlap-based feature weigh...
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Hyperspectral instruments acquire electromagnetic energy scattered within their ground instantaneous field view in hundreds of spectral channels with high spectral resolution. Very often, however, owing to low spatial resolution of the scanner or to the presence of intimate mixtures (mixing of the materials at a very small scale) in the scene, the spectral vectors (collection of signals acquire...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2018
ISSN: 2072-4292
DOI: 10.3390/rs10101546