Cross-modality learning for earth surface mapping with cloud-covered satellite optical images and radar images
There are two common kinds of images used in land classification and recognition in remote sensing technology: optical images and polarimetric synthetic aperture radar (PolSAR) images. However, optical images can be covered by clouds for a long time due to weather problems, which is one of the most...
Saved in:
Main Author: | Pi, Ziyi |
---|---|
Other Authors: | LU Yilong |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/151026 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Land cover classification with satellite optical and radar image fusion
by: Zhu, Di
Published: (2019) -
Satellite optical and radar image fusion for land cover classification
by: Zhang, Guobin
Published: (2018) -
Land cover classification using satellite optical and radar image fusion
by: Liu, Yunwei
Published: (2019) -
Re-construction of cloud-covered areas in satellite optical images based on direct translation from SAR to optical image using artificial intelligence
by: Ng, Alfred Hock Chieh
Published: (2022) -
Cloud detection and estimation for satellite optical images
by: Huang, Shuangchen
Published: (2019)