Invariant attribute profiles: A spatial-frequency joint feature extractor for hyperspectral image classification
So far, a large number of advanced techniques have been developed to enhance and
extract the spatially semantic information in hyperspectral image processing and analysis …
extract the spatially semantic information in hyperspectral image processing and analysis …
A novel method for hyperspectral image classification: Deep network with adaptive graph structure integration
Hyperspectral image (HSI) classification has always been one of the hot issues in the study
of geographic remote sensing information, and graph neural networks have attracted much …
of geographic remote sensing information, and graph neural networks have attracted much …
Local and Global Spectral Features for Hyperspectral Image Classification
Z Xu, C Su, S Wang, X Zhang - Remote Sensing, 2023 - mdpi.com
Hyperspectral images (HSI) contain powerful spectral characterization capabilities and are
widely used especially for classification applications. However, the rich spectrum contained …
widely used especially for classification applications. However, the rich spectrum contained …
Learning a deep similarity network for hyperspectral image classification
Hyperspectral image (HSI) classification is a challenging task due to subtle interclass
difference and large intraclass variability, especially when the available training samples are …
difference and large intraclass variability, especially when the available training samples are …
Graph embedding via high dimensional model representation for hyperspectral images
G Taşkın, G Camps-Valls - IEEE transactions on geoscience …, 2021 - ieeexplore.ieee.org
Learning the manifold structure of remote sensing images is of paramount relevance for
modeling and understanding processes, as well as encapsulating the high dimensionality in …
modeling and understanding processes, as well as encapsulating the high dimensionality in …
Semantic segmentation of marine remote sensing based on a cross direction attention mechanism
H Gao, L Cao, D Yu, X Xiong, M Cao - IEEE Access, 2020 - ieeexplore.ieee.org
With the development of remote sensing technology, the semantic segmentation and
recognition of various things in the ocean have become more and more frequent. Due to the …
recognition of various things in the ocean have become more and more frequent. Due to the …
Hyperspectral image classification using adaptive weighted quaternion Zernike moments
Hyperspectral image classification (HSI) has been widely used in many fields. However,
image noise, atmospheric conditions, material distribution and other factors seriously …
image noise, atmospheric conditions, material distribution and other factors seriously …
A sparse oblique-manifold nonnegative matrix factorization for hyperspectral unmixing
Hyperspectral unmixing (HU) has been one of the most significant tasks in hyperspectral
image (HSI) processing. In recent years, nonnegative matrix factorization (NMF) has …
image (HSI) processing. In recent years, nonnegative matrix factorization (NMF) has …
Deep manifold structure-preserving spectral–spatial feature extraction of hyperspectral image
The deep network has shown its superiority to extract discriminative features for
hyperspectral image (HSI) classification. However, most existing methods only exploit label …
hyperspectral image (HSI) classification. However, most existing methods only exploit label …
Functional feature extraction for hyperspectral image classification with adaptive rational function approximation
A functional feature extraction method based on rational function approximation for
hyperspectral image (HSI) classification is proposed. In digital imagery, the spectral …
hyperspectral image (HSI) classification is proposed. In digital imagery, the spectral …