Results 61 to 70 of about 6,322 (191)

Unmixing of Hyperspectral Data Using Robust Statistics-based NMF

, 2012
Mixed pixels are presented in hyperspectral images due to low spatial resolution of hyperspectral sensors. Spectral unmixing decomposes mixed pixels spectra into endmembers spectra and abundance fractions.
Ghassemian, Hassan, Rajabi, Roozbeh
core   +1 more source

Activatable smart contrast agents for photoacoustic imaging

Smart Molecules, EarlyView.
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

Hyperspectral Images Unmixing Based on Abundance Constrained Multi-Layer KNMF

IEEE Access, 2021
Due to the low spatial resolution of the sensors, the hyperspectral images contain mixed pixels. The purpose of hyperspectral unmixing is to decompose the mixed pixels into a series of endmembers and abundance fractions.
Jing Liu, You Zhang, Yi Liu, Caihong Mu
doaj   +1 more source

Sparse Unmixing using an approximate L0 Regularization [PDF]

Advances in Intelligent Systems Research, 2015
Recently, sparse unmixing focuses on finding an optimal subset of spectral signatures in a large spectral spetral library. In most previous work concerned with the sparse unmixing, the linear mixture model has been widely used to determine and quantify the abundance of materials in mixed piexels(1). In this paper, we propose a new sparse unmxing method
JianPing Xiao, Shengqian Wang, Chengzhi Deng, Tai Gao, Yang Guo   +4 more
openaire   +1 more source

Dictionary-based Tensor Canonical Polyadic Decomposition

, 2017
To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary.
Cohen, Jérémy E., Gillis, Nicolas
core   +1 more source

Nonlinear unmixing of hyperspectral images: Models and algorithms [PDF]

, 2013
When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).
Bermudez, José Carlos Moreira, Dobigeon, Nicolas, Hero, Alfred O., McLaughlin, Steve, Richard, Cédric, Tourneret, Jean-Yves   +5 more
core   +8 more sources

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

VIEW, EarlyView.
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

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

Improved Collaborative Non-Negative Matrix Factorization and Total Variation for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Hyperspectral unmixing (HSU) is an important technique of remote sensing, which estimates the fractional abundances and the mixing matrix of endmembers in each mixed pixel from the hyperspectral image.
Yuan Yuan, Zihan Zhang, Qi Wang
doaj   +1 more source

Multilayer Structured NMF for Spectral Unmixing of Hyperspectral Images

, 2015
One of the challenges in hyperspectral data analysis is the presence of mixed pixels. Mixed pixels are the result of low spatial resolution of hyperspectral sensors. Spectral unmixing methods decompose a mixed pixel into a set of endmembers and abundance
Ghassemian, Hassan, Rajabi, Roozbeh
core   +1 more source