Linear Mixing Model Performance with Nonlinear Effects in Hyperspectral Sub-Pixel Target Detection-Reference-Cited by-同舟云学术

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Linear Mixing Model Performance with Nonlinear Effects in Hyperspectral Sub-Pixel Target Detection

Published:2023-07-16 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Maloney Colin J.¹,Kerekes John P.¹,Ientilucci Emmett J.¹,Cañas Chase¹

Affiliation:

1. Rochester Institute of Technology Chester F. Carlson Center for Imaging Science,Rochester,NY,14623

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282468.pdf?arnumber=10282468

Reference8 articles.

1. DIRSIG5: Next-Generation Remote Sensing Data and Image Simulation Framework

2. The Design and Implementation of GRIT-T: RIT’s Next-generation Field Portable Goniometer System;harms;Ph D thesis,2016

3. MODTRAN6: a major upgrade of the MODTRAN radiative transfer code;berk;SPIE,2014

4. Hyperspectral Remote Sensing

5. Empirical validation of a hyperspectral systems model for subpixel target detection using data from a new UAS field collection;cañas;SPIE,0

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