Ssumamba: Spatial-spectral selective state space model for hyperspectral image denoising
Denoising is a crucial preprocessing step for hyperspectral images (HSIs) due to noise
arising from intraimaging mechanisms and environmental factors. Long-range spatial …
arising from intraimaging mechanisms and environmental factors. Long-range spatial …
Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformer
Hyperspectral images (HSIs) often suffer from noise arising from both intraimaging
mechanisms and environmental factors. Leveraging domain knowledge specific to HSIs …
mechanisms and environmental factors. Leveraging domain knowledge specific to HSIs …
UAV Hyperspectral Remote Sensing Image Classification: A Systematic Review
Z Zhang, L Huang, Q Wang, L Jiang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
In recent years, significant advances in Unmanned Aerial Vehicle (UAV) technology and
hyperspectral remote sensing have spurred rapid and innovative developments in UAV …
hyperspectral remote sensing have spurred rapid and innovative developments in UAV …
Statistical texture awareness network for hyperspectral image classification
M Jin, C Wang, Y Yuan - IEEE Transactions on Geoscience and …, 2024 - ieeexplore.ieee.org
The distribution of ground objects in hyperspectral images predominantly reveals spatial
indications of both order and disorder, encapsulating a wealth of texture information. This …
indications of both order and disorder, encapsulating a wealth of texture information. This …
LGCT: Local-Global Collaborative Transformer for Fusion of Hyperspectral and Multispectral Images
With its strong capability in modeling long-range dependencies, the Transformer achieves
competitive performance in hyperspectral image (HSI) and multispectral image (MSI) fusion …
competitive performance in hyperspectral image (HSI) and multispectral image (MSI) fusion …
Hierarchical One-Class Detection for Hyperspectral Image Classification with Background
Hyperspectral image classification (HSIC) has received considerable interest in recent years
where most techniques are developed to classify images with background (BKG) removed …
where most techniques are developed to classify images with background (BKG) removed …
Iterative Low-Rank Network for Hyperspectral Image Denoising
Hyperspectral image (HSI) denoising is a crucial preprocessing step for subsequent tasks.
The clean HSI usually reside in a low-dimensional subspace, which can be captured by low …
The clean HSI usually reside in a low-dimensional subspace, which can be captured by low …
Active Learning-based Spectral-Spatial Classification for Discriminating Tree Species in Hyperspectral Images
F Tong, Y Zhang - IEEE Journal of Selected Topics in Applied …, 2024 - ieeexplore.ieee.org
Exploiting spectral–spatial information and reducing the number of required training
samples are important for improving tree species classification performance in hyperspectral …
samples are important for improving tree species classification performance in hyperspectral …