Results 51 to 60 of about 9,466 (207)
HYPERSPECTRAL IMAGE RESOLUTION ENHANCEMENT BASED ON SPECTRAL UNMIXING AND INFORMATION FUSION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels. Spectral unmixing methods can be
J. Bieniarz +4 more
doaj +1 more source
Robust Hyperspectral Unmixing With Correntropy-Based Metric
IEEE Transactions on Image Processing, 2015 Hyperspectral unmixing is one of the crucial steps for many hyperspectral applications. The problem of hyperspectral unmixing has proven to be a difficult task in unsupervised work settings where the endmembers and abundances are both unknown. What is more, this task becomes more challenging in the case that the spectral bands are degraded with noise ...
Wang, Ying +3 more
openaire +3 more sources
Advanced Intelligent Discovery, EarlyView.Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Generalized linear mixing model accounting for endmember variability
, 2017 Endmember variability is an important factor for accurately unveiling vital information relating the pure materials and their distribution in hyperspectral images.
Bermudez, José Carlos Moreira +2 more
core +1 more source
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
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Advanced Intelligent Discovery, EarlyView.Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Adaptive Graph Regularized Multilayer Nonnegative Matrix Factorization for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Hyperspectral unmixing is an important technique for remote sensing image analysis. Among various unmixing techniques, nonnegative matrix factorization (NMF) shows unique advantage in providing a unified solution with well physical interpretation.
Lei Tong +4 more
doaj +1 more source
IET Image Processing, 2022 Although hyperspectral data, especially spaceborne images, are rich in spectral information, their spatial resolution is usually low due to the limitation of sensor design and other factors.
Haoyang Yu +5 more
doaj +1 more source
GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection
, 2019 Change detection (CD) is an important application of remote sensing, which provides timely change information about large-scale Earth surface. With the emergence of hyperspectral imagery, CD technology has been greatly promoted, as hyperspectral data ...
Du, Qian +9 more
core +1 more source
Spectral mixture analysis of EELS spectrum-images [PDF]
, 2012 Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging.
Brun, Nathalie, Dobigeon, Nicolas
core +3 more sources