Results 1 to 10 of about 19,235 (216)
SUFI: an automated approach to spectral unmixing of fluorescent multiplex images captured in mouse and post-mortem human brain tissues [PDF]
BMC Neuroscience, 2023 Background Multispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample.
Vijay Sadashivaiah +9 more
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Spectral Unmixing with Multiple Dictionaries [PDF]
IEEE Geoscience and Remote Sensing Letters, 2017 Spectral unmixing aims at recovering the spectral signatures of materials, called endmembers, mixed in a hyperspectral or multispectral image, along with their abundances.
Cohen, Jeremy E., Gillis, Nicolas
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Dynamical spectral unmixing of multitemporal hyperspectral images [PDF]
IEEE Transactions on Image Processing, 2015 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.
Chanussot, Jocelyn +2 more
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Spectral Unmixing via Data-guided Sparsity [PDF]
IEEE Transactions on Image Processing, 2014 Hyperspectral unmixing, the process of estimating a common set of spectral bases and their corresponding composite percentages at each pixel, is an important task for hyperspectral analysis, visualization and understanding.
Fan, Bin +5 more
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Spectral unmixing of Multispectral Lidar signals [PDF]
IEEE Transactions on Signal Processing, 2015 In this paper, we present a Bayesian approach for spectral unmixing of multispectral Lidar (MSL) data associated with surface reflection from targeted surfaces composed of several known materials.
Altmann, Yoann +2 more
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Spectral Unmixing of Hyperspectral Remote Sensing Imagery via Preserving the Intrinsic Structure Invariant [PDF]
Sensors, 2018 Hyperspectral unmixing, which decomposes mixed pixels into endmembers and corresponding abundance maps of endmembers, has obtained much attention in recent decades. Most spectral unmixing algorithms based on non-negative matrix factorization (NMF) do not
Yang Shao +3 more
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Robust Linear Spectral Unmixing using Anomaly Detection [PDF]
IEEE Transactions on Computational Imaging, 2015 This paper presents a Bayesian algorithm for linear spectral unmixing of hyperspectral images that accounts for anomalies present in the data. The model proposed assumes that the pixel reflectances are linear mixtures of unknown endmembers, corrupted by ...
Altmann, Yoann +2 more
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DISTRIBUTED UNMIXING OF HYPERSPECTRAL DATAWITH SPARSITY CONSTRAINT [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in
S. Khoshsokhan, R. Rajabi, H. Zayyani
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Robust blind spectral unmixing for fluorescence microscopy using unsupervised learning. [PDF]
PLoS ONE, 2019 Due to the overlapping emission spectra of fluorophores, fluorescence microscopy images often have bleed-through problems, leading to a false positive detection.
Tristan D McRae +3 more
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Remote Sensing, 2023 Spectral unmixing is one of the prime topics in hyperspectral image analysis, as images often contain multiple sources of spectra. Spectral variability is one of the key factors affecting unmixing accuracy, since spectral signatures are affected by ...
Ying Cheng +3 more
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