Results 71 to 80 of about 3,939 (225)

Efficient Progressive Mamba Model for Hyperspectral Sequence Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, deep learning-based hyperspectral unmixing has increasingly incorporated spatial information to improve performance. However, the extent of spatial information introduced involves a complex tradeoff: too little offers limited gains ...
Yang Liu, Shujun Liu, Huajun Wang
doaj   +1 more source

A Spectral Unmixing Method by Maximum Margin Criterion and Derivative Weights to Address Spectral Variability in Hyperspectral Imagery

Remote Sensing, 2019
Limited to the low spatial resolution of the hyperspectral imaging sensor, mixed pixels are inevitable in hyperspectral images. Therefore, to obtain the endmembers and corresponding fractions in mixed pixels, hyperspectral unmixing becomes a hot spot in ...
Yang Shao, Jinhui Lan
doaj   +1 more source

Pixel-to-Abundance Translation: Conditional Generative Adversarial Networks Based on Patch Transformer for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Spectral unmixing is a significant challenge in hyperspectral image processing. Existing unmixing methods utilize prior knowledge about the abundance distribution to solve the regularization optimization problem, where the difficulty lies in choosing ...
Li Wang, Xiaohua Zhang, Jinhua Zhang, Hua Dong, Hongyun Meng, Licheng Jiao   +5 more
doaj   +1 more source

Shortwave Infrared Microimaging Spectroscopy of the Martian Meteorites

Journal of Geophysical Research: Planets, Volume 131, Issue 3, March 2026.
Abstract Until samples from the Martian surface are successfully brought to Earth, meteorites represent the only opportunity to perform laboratory analyses on Martian material. Microimaging spectroscopy of the Martian meteorite suite provides a valuable means to better understand infrared data collected remotely from the Martian surface. This rapid and
J. K. Miura, B. L. Ehlmann, R. Greenberger, E. Cutts   +3 more
wiley   +1 more source

CResDAE: A Deep Autoencoder with Attention Mechanism for Hyperspectral Unmixing

Remote Sensing
Hyperspectral unmixing aims to extract pure spectral signatures (endmembers) and estimate their corresponding abundance fractions from mixed pixels, enabling quantitative analysis of surface material composition.
Chong Zhao, Jinlin Wang, Qingqing Qiao, Kefa Zhou, Jiantao Bi, Qing Zhang, Wei Wang, Dong Li, Tao Liao, Chao Li, Heshun Qiu, Guangjun Qu   +11 more
doaj   +1 more source

Hyperspectral Unmixing With Multi-Scale Convolution Attention Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing is to decompose the mixed pixel into the spectral signatures (endmembers) with their corresponding abundances. However, the ignorance of endmember variability in hyperspectral unmixing results in low performance.
Sheng Hu, Huali Li
doaj   +1 more source

Bayesian Nonparametric Unmixing of Hyperspectral Images

CoRR, 2017
Hyperspectral imaging is an important tool in remote sensing, allowing for accurate analysis of vast areas. Due to a low spatial resolution, a pixel of a hyperspectral image rarely represents a single material, but rather a mixture of different spectra. HSU aims at estimating the pure spectra present in the scene of interest, referred to as endmembers,
Jürgen T. Hahn, Abdelhak M. Zoubir
openaire   +2 more sources

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

Tissue Classification of Breast Cancer by Hyperspectral Unmixing. [PDF]

Cancers (Basel), 2023
Jong LS, Post AL, Veluponnar D, Geldof F, Sterenborg HJCM, Ruers TJM, Dashtbozorg B.   +6 more
europepmc   +1 more source

Dual-View Hyperspectral Anomaly Detection via Spatial Consistency and Spectral Unmixing [PDF]

, 2023
Jingyan Zhang, Xiangrong Zhang, Licheng Jiao   +2 more
openalex   +1 more source