Quantitative Reconstruction and Denoising Method HyBER for Hyperspectral Image Data and Its Application to CRISM

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume	12
DOIs	https://doi.org/10.1109/JSTARS.2019.2900644
State	Published - Apr 2019

Disciplines

@article{73025da10272489ca0791a79d2f96446,

title = "Quantitative Reconstruction and Denoising Method HyBER for Hyperspectral Image Data and Its Application to CRISM",

author = "Linyun He and Joseph O'Sullivan and Politte, \{Daniel V.\} and Powell, \{Kathryn E.\} and Arvidson, \{Raymond E.\}",

year = "2019",

month = apr,

doi = "10.1109/JSTARS.2019.2900644",

language = "American English",

volume = "12",

journal = "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing",

}

TY - JOUR

T1 - Quantitative Reconstruction and Denoising Method HyBER for Hyperspectral Image Data and Its Application to CRISM

AU - He, Linyun

AU - O'Sullivan, Joseph

AU - Politte, Daniel V.

AU - Powell, Kathryn E.

AU - Arvidson, Raymond E.

PY - 2019/4

Y1 - 2019/4

UR - https://ieeexplore-ieee-org.proxy.mul.missouri.edu/abstract/document/8672185/

U2 - 10.1109/JSTARS.2019.2900644

DO - 10.1109/JSTARS.2019.2900644

M3 - Article

VL - 12

JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

ER -