Results 61 to 70 of about 423,442 (225)
Spectral Unmixing with Multiple Dictionaries
, 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
core +2 more sources
Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix Factorization [PDF]
, 2013 In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subset of the columns of the input nonnegative data matrix containing all columns), which is ...
Gillis, Nicolas, Vavasis, Stephen A.
core +2 more sources
Correlative Imaging Platform Linking Taste Cell Function to Molecular Identity
Advanced Science, EarlyView.A correlative imaging platform is developed to study how individual taste cells respond to different taste qualities. By linking cellular activity with molecular identity and environmental context, dual‐tuned taste cells capable of detecting both sweet and umami stimuli are identified.
Sungho Lee +6 more
wiley +1 more source
Distributed Unmixing of Hyperspectral Data With Sparsity Constraint
, 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
Khoshsokhan, Sara +2 more
core +2 more sources
Photoacoustic Microscopy for Multiscale Biological System Visualization and Clinical Translation
Advanced Science, EarlyView.Photoacoustic microscopy (PAM) is a powerful biomedical imaging tool renowned for its non‐invasiveness and high resolution. This review synthesizes recent technological advances and highlights their broad applications from cellular and organ‐level to whole‐animal imaging.
Tingting Wang +3 more
wiley +1 more source
A Multi-Attention Autoencoder for Hyperspectral Unmixing Based on the Extended Linear Mixing Model
Remote Sensing, 2023 Hyperspectral unmixing, which decomposes mixed pixels into the endmembers and corresponding abundances, is an important image process for the further application of hyperspectral images (HSIs).
Lijuan Su, Jun Liu, Yan Yuan, Qiyue Chen
doaj +1 more source
A Few Photons Among Many: Unmixing Signal and Noise for Photon-Efficient Active Imaging [PDF]
, 2016 Conventional LIDAR systems require hundreds or thousands of photon detections to form accurate depth and reflectivity images. Recent photon-efficient computational imaging methods are remarkably effective with only 1.0 to 3.0 detected photons per pixel ...
Goyal, Vivek K, Rapp, Joshua
core +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Adaptive multiscale sparse unmixing for hyperspectral remote sensing image
Computer Science and Information Systems, 2023 Sparse unmixing of hyperspectral images aims to separate the endmembers and estimate the abundances of mixed pixels. This approach is the essential step for many applications involving hyperspectral images. The multi scale spatial sparse hyperspectral
Yalan Li +6 more
semanticscholar +1 more source
Spectral Unmixing via Data-guided Sparsity
, 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
core +1 more source