Learning-Based Near-Infrared Band Simulation with Applications on Large-Scale Landcover Classification
Multispectral sensors are important instruments for Earth observation. In remote sensing applications, the near-infrared (NIR) band, together with the visible spectrum (RGB), provide abundant information about ground objects. However, the NIR band is typically not available on low-cost camera system...
Main Authors: | Reinartz, P. (Author), Tian, J. (Author), Yuan, X. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI
2023
|
Subjects: | |
Online Access: | View Fulltext in Publisher View in Scopus |
Similar Items
-
Semisupervised Remote Sensing Image Fusion Using Multiscale Conditional Generative Adversarial Network With Siamese Structure
by: Xin Jin, et al.
Published: (2021-01-01) -
A Classified Adversarial Network for Multi-Spectral Remote Sensing Image Change Detection
by: Yue Wu, et al.
Published: (2020-06-01) -
An Adversarial Generative Network for Crop Classification from Remote Sensing Timeseries Images
by: Jingtao Li, et al.
Published: (2021-12-01) -
Hyperspectral Remote Sensing Imagery Generation From RGB Images Based on Joint Discrimination
by: Liqin Liu, et al.
Published: (2021-01-01) -
Study of Adversarial Machine Learning with Infrared Examples for Surveillance Applications
by: DeMarcus Edwards, et al.
Published: (2020-08-01)