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Nonlinear unmixing of minerals based on the log and continuum removal model
European Journal of Remote Sensing, 2019 Spectral mixing models for minerals can be complex, and choosing the right unmixing model is indispensable to ensure the accuracy of spectral unmixing. Continuum removal (CR) and natural log operation have the potential to eliminate nonlinear effects in ...
Hengqian Zhao, Xuesheng Zhao
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Dynamical Spectral Unmixing of Multitemporal Hyperspectral Images [PDF]
IEEE Transactions on Image Processing, 2016 In this paper, we consider the problem of unmixing a time series of hyperspectral images. We propose a dynamical model based on linear mixing processes at each time instant. The spectral signatures and fractional abundances of the pure materials in the scene are seen as latent variables, and assumed to follow a general dynamical structure.
Henrot, Simon +2 more
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Sensors, 2020 Multispectral photoacoustic imaging has been widely explored as an emerging tool to visualize and quantify tissue chromophores noninvasively. This modality can capture the spectral absorption signature of prominent tissue chromophores, such as oxygenated,
Valeria Grasso +2 more
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UNMIX-ME: spectral and lifetime fluorescence unmixing via deep learning
Biomedical Optics Express, 2020 Hyperspectral fluorescence lifetime imaging allows for the simultaneous acquisition of spectrally resolved temporal fluorescence emission decays. In turn, the acquired rich multidimensional data set enables simultaneous imaging of multiple fluorescent species for a comprehensive molecular assessment of biotissues.
Jason T. Smith +2 more
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Least Angle Regression-Based Constrained Sparse Unmixing of Hyperspectral Remote Sensing Imagery
Remote Sensing, 2018 Sparse unmixing has been successfully applied in hyperspectral remote sensing imagery analysis based on a standard spectral library known in advance. This approach involves reformulating the traditional linear spectral unmixing problem by finding the ...
Ruyi Feng, Lizhe Wang, Yanfei Zhong
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SSANet: An Adaptive Spectral–Spatial Attention Autoencoder Network for Hyperspectral Unmixing
Remote Sensing, 2023 Convolutional neural-network-based autoencoders, which can integrate the spatial correlation between pixels well, have been broadly used for hyperspectral unmixing and obtained excellent performance.
Jie Wang +7 more
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Online spectral unmixing in gamma-ray spectrometry
Applied Radiation and Isotopes, 2023 We introduced in a previous paper a time-dependent full-spectrum analysis algorithm speeding up the estimation of the activity of the radionuclides present in a sample. In this paper, we present a new version of the algorithm allowing online estimation.
Malfrait, Paul +2 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral spectral mixture analysis (SMA), which intends to decompose mixed pixels into a collection of endmembers weighted by their corresponding fraction abundances, has been successfully used to tackle mixed-pixel problem in hyperspectral remote ...
Ge Zhang, Shaohui Mei, Yan Feng, Qian Du
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A cascaded autoencoder unmixing network for Hyperspectral anomaly detection
International Journal of Applied Earth Observations and GeoinformationHyperspectral anomaly detection (HAD) is challenging especially when anomalies are presented in sub-pixel form.The spectral signatures of anomalies in mixed pixels are mixed with those of background, making anomalies difficult to be distinguished from ...
Kun Li +4 more
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Spectral unmixing: analysis of performance in the olfactory bulb in vivo. [PDF]
PLoS ONE, 2009 BACKGROUND: The generation of transgenic mice expressing combinations of fluorescent proteins has greatly aided the reporting of activity and identification of specific neuronal populations. Methods capable of separating multiple overlapping fluorescence
Mathieu Ducros +5 more
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