activity
20122019
most citedSpectral Unmixing of Hyperspectral Imagery using Multilayer NMF

166 citations · 167 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2019

Clustered Multitask Nonnegative Matrix Factorization for Spectral Unmixing of Hyperspectral Data

Sara Khoshsokhan, Roozbeh Rajabi, Hadi Zayyani

In this paper, the new algorithm based on clustered multitask network is proposed to solve spectral unmixing problem in hyperspectral imagery. In the proposed algorithm, the cluste…

cs.CV2019

Sparsity Constrained Distributed Unmixing of Hyperspectral Data

Sara Khoshsokhan, Roozbeh Rajabi, Hadi Zayyani

Spectral unmixing (SU) is a technique to characterize mixed pixels in hyperspectral images measured by remote sensors. Most of the spectral unmixing algorithms are developed using…

cs.CV20171 cited

Distributed Unmixing of Hyperspectral Data With Sparsity Constraint

Sara Khoshsokhan, Roozbeh Rajabi, Hadi Zayyani

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, ac…

cs.CV2015

Multilayer Structured NMF for Spectral Unmixing of Hyperspectral Images

Roozbeh Rajabi, Hassan Ghassemian

One of the challenges in hyperspectral data analysis is the presence of mixed pixels. Mixed pixels are the result of low spatial resolution of hyperspectral sensors. Spectral unmix…

cs.CV2014166 cited

Spectral Unmixing of Hyperspectral Imagery using Multilayer NMF

Roozbeh Rajabi, Hassan Ghassemian

Hyperspectral images contain mixed pixels due to low spatial resolution of hyperspectral sensors. Spectral unmixing problem refers to decomposing mixed pixels into a set of endmemb…

cs.CV2012

Unmixing of Hyperspectral Data Using Robust Statistics-based NMF

Roozbeh Rajabi, Hassan Ghassemian

Mixed pixels are presented in hyperspectral images due to low spatial resolution of hyperspectral sensors. Spectral unmixing decomposes mixed pixels spectra into endmembers spectra…