Results 11 to 20 of about 9,243 (189)
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
openaire +7 more sources
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
doaj +4 more sources
SIP-SRS Imaging of Cell Wall Synthesis Identifies a Synergy between Micafungin and Amphotericin B. [PDF]
Adv Sci (Weinh)We employed glucose‐d7–based stable isotope probe‐assisted SRS microscopy (SIP‐SRS) C–D imaging to visualize fungal cell wall synthesis and remodeling under antifungal treatment. Amphotericin B (AmB) induced notable daughter cell wall thickening, prompting a combinational therapy with AmB and micafungin.
Zhang M +6 more
europepmc +2 more sources
IEEE Access, 2021 Hyperspectral unmixing has attracted considerable attentions in recent years and some promising algorithms have been developed. In this paper, collaborative representation–based unmixing (CRU) for hyperspectral images is proposed.
Jing Wang
doaj +1 more source
A New Deep Convolutional Network for Effective Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral unmixing extracts pure spectral constituents (endmembers) and their corresponding abundance fractions from remotely sensed scenes. Most traditional hyperspectral unmixing methods require the results of other endmember extraction algorithms ...
Xuanwen Tao +7 more
doaj +1 more source
How Hyperspectral Image Unmixing and Denoising Can Boost Each Other
Remote Sensing, 2020 Hyperspectral linear unmixing and denoising are highly related hyperspectral image (HSI) analysis tasks. In particular, with the assumption of Gaussian noise, the linear model assumed for the HSI in the case of low-rank denoising is often the same as the
Behnood Rasti +3 more
doaj +1 more source
Hyperspectral Imaging Techniques for Lyophilization: Advances in Data-Driven Modeling Strategies and Applications. [PDF]
Adv Sci (Weinh)Lyophilization is a key process used in the production of biotherapeutic products. This article reviews and discusses the application of HSI on lyophilization, and the strategies that use the resulting data to build models. It is intended to provide guidance and insights for non‐specialist researchers and engineers into leveraging HSI and the data ...
Yu H +5 more
europepmc +2 more sources
Maximum Likelihood Estimation Based Nonnegative Matrix Factorization for Hyperspectral Unmixing
Remote Sensing, 2021 Hyperspectral unmixing (HU) is a research hotspot of hyperspectral remote sensing technology. As a classical HU method, the nonnegative matrix factorization (NMF) unmixing method can decompose an observed hyperspectral data matrix into the product of two
Qin Jiang +4 more
doaj +1 more source
ASSESSING AND COMPARING THE PERFORMANCE OF ENDMEMBER EXTRACTION METHODS IN MULTIPLE CHANGE DETECTION USING HYPERSPECTRAL DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Endmember extraction is a process to identify the hidden pure source signals from the mixture. Endmember finding has become increasingly important in hyperspectral data exploitation because endmembers can be used to specify unknown particular spectral ...
H. Jafarzadeh, M. Hasanlou
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Sparse unmixing with a semisupervised fashion has been applied to hyperspectral remote sensing imagery. However, the imprecise spatial contextual information, the lack of global feature and the high mutual coherences of a spectral library greatly limit ...
Hongjun Su +3 more
doaj +1 more source