Results 81 to 90 of about 296,705 (175)

Mapping Peatlands Combing Deep Learning With Sparse Spectral Unmixing Based on Zhuhai-1 Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
The mixed pixel problem, arising from the complex vegetation types of peatlands, poses a significant challenge for remote sensing-based peatland mapping.
Yulin Xu, Xiaodong Na
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

Double Regression Sparse Unmixing for Hyperspectral Image

, 2020
This file contains MATLAB code and data set, which is about “Double Regression Sparse Unmixing for Hyperspectral ...
Zhang Shuaiyang
core   +1 more source

Hyperspectral unmixing using weighted sparse regression with total variation regularization

, 2022
Spectral unmixing aims at identifying the pure spectral signatures in hyperspectral images and simultaneously estimating their proportions in each pixel of the scene.
Ma, Zheng, Hu, Jianming, Ren, Longfei, Bruzzone, Lorenzo, Bovolo, Francesca   +4 more
core   +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

Independent Component Analysis (ICA) as a Superior Atmospheric Correction Method for InSAR Time Series

Journal of Geophysical Research: Solid Earth, Volume 131, Issue 8, August 2026.
Abstract Satellites such as the European Space Agency's Sentinel‐1 constellation allow for the creation of unprecedented volumes of Interferometric Synthetic Aperture RaDAR data that contains both deformation and atmospheric signals. Correction methods have been developed to reduce these atmospheric signals, but they do not generally perform well on ...
M. Gaddes, A. Hooper, S. Ebmeier
wiley   +1 more source

Double reweighted sparse regression for hyperspectral unmixing

, 2016
Spectral unmixing is an important technology in hyperspectral image applications. Recently, sparse regression is widely used in hyperspectral unmixing. This paper proposes a double reweighted sparse regression method for hyperspectral unmixing.
Heng-Chao Li, Liao, Wenzhi, Aleksandra Pizurica, Wenzhi Liao, Pizurica, Aleksandra, Li, Hengchao, Wang, Rui, Rui Wang   +7 more
core   +1 more source

Superpixel Weighted Low-rank and Sparse Approximation for Hyperspectral Unmixing

, 2022
We propose a superpixel weighted low-rank and sparse unmixing (SWLRSU) method for sparse unmixing. The proposed method consists of two steps. In the first step, we segment hyperspectral image into superpixels which are defined as the homogeneous regions ...
Hasari Karci (11886522), Taner Ince (11886482), Tugcan Dundar (11886487), Seydi Kacmaz (11886521)   +3 more
core   +1 more source

SCSU–GDO: Superpixel Collaborative Sparse Unmixing with Graph Differential Operator for Hyperspectral Imagery

Remote Sensing
In recent years, remarkable advancements have been achieved in hyperspectral unmixing (HU). Sparse unmixing, in which models mix pixels as linear combinations of endmembers and their corresponding fractional abundances, has become a dominant paradigm in ...
Kaijun Yang, Zhixin Zhao, Qishen Yang, Ruyi Feng   +3 more
doaj   +1 more source

Urban Land Cover Mapping from Airborne Hyperspectral Imagery Using a Fast Jointly Sparse Spectral Mixture Analysis Method

Canadian Journal of Remote Sensing, 2020
Due to the fragmented compositional structure of urban scenes, many pixels are mixtures of multiple materials even in high spatial resolution airborne hyperspectral data.
Fen Chen, Sijia Lu, Peng Zhao, Tim Van de Voorde, Wenbo Xu   +4 more
doaj   +1 more source