Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing
PV Giampouras, KE Themelis… - … on Geoscience and …, 2016 - ieeexplore.ieee.org
In a plethora of applications dealing with inverse problems, eg, image processing, social
networks, compressive sensing, and biological data processing, the signal of interest is …
networks, compressive sensing, and biological data processing, the signal of interest is …
A probabilistic joint sparse regression model for semisupervised hyperspectral unmixing
SF Seyyedsalehi, HR Rabiee… - … and Remote Sensing …, 2017 - ieeexplore.ieee.org
Semisupervised hyperspectral unmixing finds the ratio of spectral library members in the
mixture of hyperspectral pixels to find the proportion of pure materials in a natural scene …
mixture of hyperspectral pixels to find the proportion of pure materials in a natural scene …
A sparse reduced-rank regression approach for hyperspectral image unmixing
PV Giampouras, AA Rontogiannis… - … Sensing Theory and …, 2015 - ieeexplore.ieee.org
In this paper we propose a semi-supervised method for hyperspectral image unmixing.
Given a set of endmembers present in the image, we assume that (a) each pixel is …
Given a set of endmembers present in the image, we assume that (a) each pixel is …
Structured Abundance Matrix Estimation for Land Cover Hyperspectral Image Unmixing
PV Giampouras, KE Themelis… - … Sensing of Earth …, 2017 - taylorfrancis.com
Spectral unmixing (SU) of hyperspectral images (HSIs) has been in the spotlight of both
research and applications during the recent years. Abundance estimation algorithms hinge …
research and applications during the recent years. Abundance estimation algorithms hinge …