Kernel Tensor Sparse Coding Model for Precise Crop Classification of UAV Hyperspectral Image

In this letter, a kernel tensor sparse coding model (KTSCM) is proposed for precise crop classification of unmanned aerial vehicle (UAV) hyperspectral image (HSI). Benefited from the kernel tensor representation mechanism in KTSCM, which can not only improve the linear separation but also well prese...

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Vydáno v:	IEEE geoscience and remote sensing letters Ročník 20; s. 1
Hlavní autoři:	Yang, Lixia, Zhang, Rui, Bao, Yajun, Yang, Shuyuan, Jiao, Licheng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Autonomous aerial vehicles Classification Coding Computation Cost analysis Crops Dictionaries Encoding Exact solutions Hyperspectral imaging Image classification Kernel Kernel tensor sparse coding Kernels Mathematical analysis precise crop classification Tensors unmanned aerial vehicle hyperspectral image Unmanned aerial vehicles
ISSN:	1545-598X, 1558-0571
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Abstract	In this letter, a kernel tensor sparse coding model (KTSCM) is proposed for precise crop classification of unmanned aerial vehicle (UAV) hyperspectral image (HSI). Benefited from the kernel tensor representation mechanism in KTSCM, which can not only improve the linear separation but also well preserving the spatial-spectral structures of land-covers, the discriminability of UAV HSI is greatly improved. The L1-norm based tensor sparsity makes the tensor operation in KTSCM can be equivalently converted to matrix operation, which greatly reduces the computation cost. Furthermore, the analytical solution to KTSCM allows it be well optimized with very few iterations. The performance of KTSCM is assessed on two real UAV HSIs. The experimental results indicate that KTSCM can provides rapid and accurate crop classification results with limited labeled pixels and outperforms the related counterparts.
AbstractList	In this letter, a kernel tensor sparse coding model (KTSCM) is proposed for precise crop classification of unmanned aerial vehicle (UAV) hyperspectral image (HSI). Benefiting from the kernel tensor representation mechanism in KTSCM, which can not only improve the linear separation but also preserve the spatial-spectral structures of land covers, the discriminability of UAV HSI is greatly improved. The L1-norm-based tensor sparsity makes the tensor operation in KTSCM be equivalently converted to matrix operation, which greatly reduces the computation cost. Furthermore, the analytical solution to KTSCM allows it to be well-optimized with very few iterations. The performance of KTSCM is assessed on two real UAV HSIs. The experimental results indicate that KTSCM can provide rapid and accurate crop classification results with limited labeled pixels and outperforms the related counterparts. In this letter, a kernel tensor sparse coding model (KTSCM) is proposed for precise crop classification of unmanned aerial vehicle (UAV) hyperspectral image (HSI). Benefited from the kernel tensor representation mechanism in KTSCM, which can not only improve the linear separation but also well preserving the spatial-spectral structures of land-covers, the discriminability of UAV HSI is greatly improved. The L1-norm based tensor sparsity makes the tensor operation in KTSCM can be equivalently converted to matrix operation, which greatly reduces the computation cost. Furthermore, the analytical solution to KTSCM allows it be well optimized with very few iterations. The performance of KTSCM is assessed on two real UAV HSIs. The experimental results indicate that KTSCM can provides rapid and accurate crop classification results with limited labeled pixels and outperforms the related counterparts.
Author	Yang, Shuyuan Yang, Lixia Zhang, Rui Jiao, Licheng Bao, Yajun
Author_xml	– sequence: 1 givenname: Lixia orcidid: 0000-0001-5518-9195 surname: Yang fullname: Yang, Lixia organization: School of Mathematics and Statistics, NingXia University, Yinchuan, Ningxia, China – sequence: 2 givenname: Rui surname: Zhang fullname: Zhang, Rui organization: School of Mathematics and Statistics, NingXia University, Yinchuan, Ningxia, China – sequence: 3 givenname: Yajun surname: Bao fullname: Bao, Yajun organization: School of Mathematics and Statistics, NingXia University, Yinchuan, Ningxia, China – sequence: 4 givenname: Shuyuan orcidid: 0000-0002-4796-5737 surname: Yang fullname: Yang, Shuyuan organization: School of Artificial Intelligence, Xidian University, Xi'an, Shaanxi, China – sequence: 5 givenname: Licheng orcidid: 0000-0003-3354-9617 surname: Jiao fullname: Jiao, Licheng organization: School of Artificial Intelligence, Xidian University, Xi'an, Shaanxi, China
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SubjectTerms	Autonomous aerial vehicles Classification Coding Computation Cost analysis Crops Dictionaries Encoding Exact solutions Hyperspectral imaging Image classification Kernel Kernel tensor sparse coding Kernels Mathematical analysis precise crop classification Tensors unmanned aerial vehicle hyperspectral image Unmanned aerial vehicles
Title	Kernel Tensor Sparse Coding Model for Precise Crop Classification of UAV Hyperspectral Image
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