Results 71 to 80 of about 1,157 (179)

Activatable smart contrast agents for photoacoustic imaging

Smart Molecules, Volume 4, Issue 2, June 2026.
This review highlights recent advances in smart activatable photoacoustic imaging (PAI) contrast agents, which dynamically modulate their optical properties in response to external stimuli or microenvironmental cues. It discusses their molecular design, activation mechanisms, biomedical applications, and future prospects for clinically tailored use ...
Donghyeon Oh, Jihye Lee, Suyoung Park, Juyoung Yoon, Won Jong Kim, Chulhong Kim   +5 more
wiley   +1 more source

Centralized Collaborative Sparse Unmixing for Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017
Spectral unmixing is very important in hyperspectral image analysis and processing, which aims at identifying the constituent spectra (i.e., endmembers) and estimating their fractional abundances from the mixed pixels. In recent years, sparse unmixing has received considerable interest.
Rui Wang 0090, Heng-Chao Li 0001, Wenzhi Liao, Xin Huang 0002, Wilfried Philips   +4 more
openaire   +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

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

Synthesizing hyperspectral Data using generative Models to train spectral Unmixing Methods for low-cost Crop Residue Cover Mapping [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
The spectral range of the Field Imaging Nanosatellite for Crop residue Hyperspectral Mapping (FINCH), developed by the University of Toronto Aerospace Team’s Space System Division, poses significant challenges for hyperspectral unmixing to ...
E. Artan, E. Artan, S. Chen, S. Chen, A. Peng, A. Peng, S. A. Karya, S. A. Karya, K. Thiha, K. Thiha   +9 more
doaj   +1 more source

Fractional Impervious Surface Mapping on Multispectral Images With Visible Shadows via a Bundle-Based Sparse Unmixing Model

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Impervious surface abundance (ISA) is an important indicator for monitoring urbanization and environmental disaster management processes. Commonly used spectral unmixing techniques extract ISA in the form of mixed pixels; however, in previous ...
Yanze Liu, Dacheng Li, Wei Xiong, Qijin Han, Lingling Ma   +4 more
doaj   +1 more source

Blind Hyperspectral Unmixing With Integrated Nonsmooth and CEM Spatial Constraints

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral blind unmixing serves as a key technique in remote sensing image processing. Its core value lies in the ability to extract endmember spectral signatures and invert abundance fractions from mixed pixels without relying on prior endmember ...
Shaoquan Zhang, Kexing Li, Xinyi Zhou, Fan Li, Pengfei Lai, Lianhui Liang, Chengzhi Deng, Shengqian Wang   +7 more
doaj   +1 more source

Temperature scaling unmixing framework based on convolutional autoencoder

International Journal of Applied Earth Observations and Geoinformation
Hyperspectral unmixing is a key technology in the development of remote sensing applications. However, since both endmembers and abundances are unknown, unmixing is a non-convex problem with a large solution space. To solve this, existing methods usually
Jin Xu, Mingming Xu, Shanwei Liu, Hui Sheng, Zhiru Yang   +4 more
doaj   +1 more source

A Novel Sub-Abundance Map Regularized Sparse Unmixing Framework Based on Dynamic Abundance Subspace Awareness

Mathematics
Sparse unmixing (SU) has become a research hotspot in hyperspectral image (HSI) analysis in recent years due to its interpretable physical mechanisms and engineering practicality.
Kewen Qu, Fangzhou Luo, Huiyang Wang, Wenxing Bao   +3 more
doaj   +1 more source

Poster Sessions

HemaSphere, Volume 10, Issue S1, June 2026.
wiley   +1 more source