Results 71 to 80 of about 919,951 (170)
Fast and Structured Block-Term Tensor Decomposition for Hyperspectral Unmixing
The block-term tensor decomposition model with multilinear rank-$(L_{r},L_{r},1)$ terms (or the “${\mathsf{LL1}}$ tensor decomposition” in short) offers a valuable alternative formulation for hyperspectral unmixing (HU), which ensures the ...
Meng Ding, Xiao Fu, Xi-Le Zhao
doaj +1 more source
SSF-Net: A Spatial–Spectral Features Integrated Autoencoder Network for Hyperspectral Unmixing
In recent years, deep learning has received tremendous attention in the field of hyperspectral unmixing (HU) due to its powerful learning capabilities.
Bin Wang +4 more
doaj +1 more source
An Outlier-Insensitive Unmixing Algorithm With Spatially Varying Hyperspectral Signatures
Effective hyperspectral unmixing (HU) is essential to the estimation of the underlying materials' signatures (endmember signatures) and their spatial distributions (abundance maps) from a given image (data) of a hyperspectral scene.
Yao-Rong Syu +2 more
doaj +1 more source
GAUSS: Guided Encoder-Decoder Architecture for Hyperspectral Unmixing with Spatial Smoothness [PDF]
In recent hyperspectral unmixing (HU) literature, the application of deep learning (DL) has become more prominent, especially with the autoencoder (AE) architecture.
Ramanayake, Lakshitha +8 more
core
Compressed sensing based hyperspectral unmixing
In hyperspectral images the measured spectra for each pixel can be modeled as convex combination of small number of endmember spectra. Since the measured structure contains only a few of possible responses out of possibly many materials sparsity based ...
Albayrak, R. Tufan +5 more
core +2 more sources
Compact Spectral Imaging: A Review of Miniaturized and Integrated Systems
This review explores the rapid shift toward compact spectral imaging systems by examining four key design paradigms: Do‐It‐Yourself (DIY) platforms, freeform optics, filter‐on‐chip integration, and multifunctional metasurfaces. The discussion highlights critical applications in medicine, agriculture, and environmental monitoring, providing comparative ...
Sani Mukhtar, Amir Arbabi, Jaime Viegas
wiley +1 more source
Abstract Effective sediment monitoring is crucial for managing dynamic river environments where suspended sediment transport varies over time. However, manual sampling and turbidity sensor‐based methods provide limited spatial coverage and can be labor‐intensive.
Siyoon Kwon +3 more
wiley +1 more source
ABSTRACT In recent years, camouflage technology has evolved from single‐spectral‐band applications to multifunctional and multispectral implementations. Hyperspectral imaging has emerged as a powerful technique for target identification due to its capacity to capture both spectral and spatial information.
Jiale Zhao +6 more
wiley +1 more source
Monitoring and Modeling the Soil‐Plant System Toward Understanding Soil Health
Abstract The soil health assessment has evolved from focusing primarily on agricultural productivity to an integrated evaluation of soil biota and biotic processes that impact soil properties. Consequently, soil health assessment has shifted from a predominantly physicochemical approach to incorporating ecological, biological and molecular microbiology
Yijian Zeng +8 more
wiley +1 more source
Hyperspectral image restoration using noise gradient and dual priors under mixed noise conditions
Abstract Images obtained from hyperspectral sensors provide information about the target area that extends beyond the visible portions of the electromagnetic spectrum. However, due to sensor limitations and imperfections during the image acquisition and transmission phases, noise is introduced into the acquired image, which can have a negative impact ...
Hazique Aetesam +2 more
wiley +1 more source

