Results 41 to 50 of about 1,157 (179)

Establishing Monthly Benchmarks for Erosion Control and Vegetation Restoration Targets Across the Loess Plateau

Land Degradation &Development, EarlyView.
ABSTRACT Establishing scientifically grounded soil erosion control targets and feasible vegetation restoration strategies is crucial for high quality development of the Chinese Loess Plateau which is severely affected by soil erosion. Currently, the commonly used tolerable soil loss (TSL) is inadequate for addressing the spatial heterogeneity in ...
Ye Wang, Haijing Shi, Xihua Yang, Rui Li, Hongming Zhang, Jiaqiong Zhang, Wenyi Sun, Yangyang Liu, Qinggaozi Zhu, Guang Yang   +9 more
wiley   +1 more source

Hypergraph-Regularized Sparse NMF for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
Hyperspectral image (HSI) unmixing has attracted increasing research interests in recent decades. The major difficulty of it lies in that the endmembers and the associated abundances need to be separated from highly mixed observation data with few a priori information.
Wenhong Wang 0004, Yuntao Qian, Yuan Yan Tang   +2 more
openaire   +1 more source

Scalable Large Field‐of‐view 3D Photoacoustic Ultrasound Imaging With Digital Multiplexing for Human Extremities

Laser &Photonics Reviews, EarlyView.
A digitally multiplexed, large‐aperture photoacoustic and ultrasound imaging architecture is presented to overcome the fundamental limited‐view artifact inherent in conventional arrays. By significantly broadening the structural detection coverage, this scalable platform enables high‐fidelity 3D visualization of human extremities within a single ...
Sinyoung Park, Minsik Sung, Hyunhee Kim, Kijong Lee, Joongho Ahn, Eun‐Yeong Park, Sungsik Park, Hyung Ham Kim, Chulhong Kim   +8 more
wiley   +1 more source

A Multi-Attention Autoencoder for Hyperspectral Unmixing Based on the Extended Linear Mixing Model

Remote Sensing, 2023
Hyperspectral unmixing, which decomposes mixed pixels into the endmembers and corresponding abundances, is an important image process for the further application of hyperspectral images (HSIs).
Lijuan Su, Jun Liu, Yan Yuan, Qiyue Chen
doaj   +1 more source

Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe, Yazhou Sun, Sanai Li, Wenxuan Guo   +3 more
wiley   +1 more source

Robust Multiscale Spectral–Spatial Regularized Sparse Unmixing for Hyperspectral Imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With the aid of endmember spectral libraries, sparse unmixing plays a critical role in interpreting hyperspectral remote sensing data. Integrating spatial clues from hyperspectral data into sparse unmixing frameworks is pivotal for enhancing unmixing ...
Ke Wang, Lei Zhong, Jiajun Zheng, Shaoquan Zhang, Fan Li, Chengzhi Deng, Jingjing Cao, Dingli Su   +7 more
doaj   +1 more source

Subspace Structure Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Hyperspectral unmixing is a crucial task for hyperspectral images (HSIs) processing, which estimates the proportions of constituent materials of a mixed pixel. Usually, the mixed pixels can be approximated using a linear mixing model. Since each material
Lei Zhou, Xueni Zhang, Jianbo Wang, Xiao Bai, Lei Tong, Liang Zhang, Jun Zhou, Edwin Hancock   +7 more
doaj   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, Volume 2, Issue 4, August 2026.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation

Remote Sensing, 2017
In this paper, a new method is presented for spatial resolution enhancement of hyperspectral images (HSI) using spectral unmixing and a Bayesian sparse representation.
Elham Kordi Ghasrodashti, Azam Karami, Rob Heylen, Paul Scheunders   +3 more
doaj   +1 more source

SMILE: Extraction‐free submicron‐resolution mapping of lipid chain length and unsaturation by stimulated Raman imaging

VIEW, Volume 7, Issue 4, August 2026.
In this work, we develop submicron‐resolution mapping of intracellular lipid elements (SMILE) as an extraction‐free vibrational spectroscopic imaging platform based on hyperspectral stimulated Raman scattering microscopy with a spectral analysis pipeline for pixel‐resolved lipid profiling.
Yihui Zhou, Xiangjie Huang, Xingxin Liu, Ling Zhang, Jie Huang, Jing Zhao, Yongqing Zhang, Jin Zhang, Yanqing Gong, Delong Zhang, Hyeon Jeong Lee   +10 more
wiley   +1 more source