Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets
The precise classification of land covers with hyperspectral imagery (HSI) is a major
research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) …
research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) …
SpaSSA: Superpixelwise adaptive SSA for unsupervised spatial–spectral feature extraction in hyperspectral image
Singular spectral analysis (SSA) has recently been successfully applied to feature extraction
in hyperspectral image (HSI), including conventional (1-D) SSA in spectral domain and 2-D …
in hyperspectral image (HSI), including conventional (1-D) SSA in spectral domain and 2-D …
Tensor singular spectrum analysis for 3-D feature extraction in hyperspectral images
Due to the cubic structure of a hyperspectral image (HSI), how to characterize its spectral
and spatial properties in 3-D is challenging. Conventional spectral–spatial methods usually …
and spatial properties in 3-D is challenging. Conventional spectral–spatial methods usually …
Folded LDA: extending the linear discriminant analysis algorithm for feature extraction and data reduction in hyperspectral remote sensing
The rich spectral information provided by hyperspectral imaging has made this technology
very useful in the classification of remotely sensed data. However, classification of …
very useful in the classification of remotely sensed data. However, classification of …
PCA-domain fused singular spectral analysis for fast and noise-robust spectral–spatial feature mining in hyperspectral classification
The principal component analysis (PCA) and 2-D singular spectral analysis (2DSSA) are
widely used for spectral-and spatial-domain feature extraction in hyperspectral images …
widely used for spectral-and spatial-domain feature extraction in hyperspectral images …
Attention based deep convolutional U-Net with CSA optimization for hyperspectral image denoising
R Murugesan, N Nachimuthu, G Prakash - Infrared Physics & Technology, 2023 - Elsevier
Hyperspectral image (HSI) de-noising plays a significant role in HSI quality enhancement
because it consists of rich image information. Although, large amounts of information …
because it consists of rich image information. Although, large amounts of information …
Discriminative sketch topic model with structural constraint for SAR image classification
Synthetic aperture radar (SAR) image classification is an important part in the understanding
and interpretation of SAR images. Each patch in SAR images has a scene category, but …
and interpretation of SAR images. Each patch in SAR images has a scene category, but …
Characterization of the Ethanol-Water Blend by Acoustic Signature Analysis in Ultrasonic Signals
A Bernardi, LEB Da Silva, GFC Veloso… - IEEE …, 2022 - ieeexplore.ieee.org
The use of ethanol as fuel in Brazil stimulated the competition between distribution
companies and resellers, which aggravated the practice of adulteration of fuels, aiming for …
companies and resellers, which aggravated the practice of adulteration of fuels, aiming for …
Superpixel nonlocal weighting joint sparse representation for hyperspectral image classification
Joint sparse representation classification (JSRC) is a representative spectral–spatial
classifier for hyperspectral images (HSIs). However, the JSRC is inappropriate for highly …
classifier for hyperspectral images (HSIs). However, the JSRC is inappropriate for highly …
Fast and Accurate Hyperspectral Image Classification with Window Shape Adaptive Singular Spectrum Analysis
X Bai, B Qi, L Jin, G Li, J Li - Remote Sensing, 2023 - mdpi.com
Hyperspectral classification is a task of significant importance in the field of remote sensing
image processing, with attaining high precision and rapid classification increasingly …
image processing, with attaining high precision and rapid classification increasingly …