Cloud detection and estimation for satellite optical images
Cloud is a very common weather phenomenon in the world. In Singapore, it is possible that everyone will see the cloud every day. It is not bad to have the cloud over the top. However, for optical satellite images analysis, which operates tens of thousands optical images daily, cloud causes a lot...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project |
| Language: | English |
| Published: |
2019
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/78300 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Cloud is a very common weather phenomenon in the world. In Singapore, it is
possible that everyone will see the cloud every day. It is not bad to have the cloud
over the top. However, for optical satellite images analysis, which operates tens of
thousands optical images daily, cloud causes a lot of trouble.
Therefore, cloud detection and cloud masking process become an important procedure
in data preprocessing for optical satellite images.
The problem is that the existing algorithms such as Sentinel-2 are too complicated and
or too costly. They need satellite using Multi-spectral camera to record the image
daily or they need to analyze the image pixel by pixel which is not so efficient as
expectation. Meanwhile, the computer is easy to be confused by different white
objects on the land such as snow, white houses. Some of the existing technique using
rectangle to segment the cloud area from the image is useful but the shape of the
cloud is random and irregular which need more effective method to crop the cloud
out.
Our method aims to develop and apply some algorithms, with superpixels technique
and machine learning, for effectively detecting the cloud on RGB images and
evaluating application |
|---|