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6 papers
Tech Report: A Homogeneity-Based Multiscale Hyperspectral Image Representation for Sparse Spectral Unmixing
L. C. Ayres, S. J. M. de Almeida, J. C. M. Bermudez +1
Several approaches have been proposed to solve the spectral unmixing problem in hyperspectral image analysis. Among them the use of sparse regression techniques aims to characteriz…
Coupled Tensor Decomposition for Hyperspectral and Multispectral Image Fusion with Inter-Image Variability
Ricardo Augusto Borsoi, Clémence Prévost, Konstantin Usevich +3
Coupled tensor approximation has recently emerged as a promising approach for the fusion of hyperspectral and multispectral images, reconciling state of the art performance with st…
Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +6
The spectral signatures of the materials contained in hyperspectral images, also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or…
Deep Generative Endmember Modeling: An Application to Unsupervised Spectral Unmixing
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez
Endmember (EM) spectral variability can greatly impact the performance of standard hyperspectral image analysis algorithms. Extended parametric models have been successfully applie…
Low-Rank Tensor Modeling for Hyperspectral Unmixing Accounting for Spectral Variability
Tales Imbiriba, Ricardo Augusto Borsoi, José Carlos Moreira Bermudez
Traditional hyperspectral unmixing methods neglect the underlying variability of spectral signatures often observed in typical hyperspectral images (HI), propagating these missmode…
Generalized linear mixing model accounting for endmember variability
Tales Imbiriba, Ricardo Augusto Borsoi, José Carlos Moreira Bermudez
Endmember variability is an important factor for accurately unveiling vital information relating the pure materials and their distribution in hyperspectral images. Recently, the ex…