1 citations · 1 across the 3 of their papers we have counts for
5 papers · 1 filter
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…
A Data Dependent Multiscale Model for Hyperspectral Unmixing With Spectral Variability
Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez
Spectral variability in hyperspectral images can result from factors including environmental, illumination, atmospheric and temporal changes. Its occurrence may lead to the propaga…
A Low-rank Tensor Regularization Strategy for Hyperspectral Unmixing
Tales Imbiriba, Ricardo Augusto Borsoi, José Carlos Moreira Bermudez
Tensor-based methods have recently emerged as a more natural and effective formulation to address many problems in hyperspectral imaging. In hyperspectral unmixing (HU), low-rank c…
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…