- Tytuł:
- Restoration of Remote Satellite Sensing Images using Machine and Deep Learning : a Survey
- Autorzy:
-
Abdellaoui, Meriem
Benabdelkader, Souad
Assas, Ouarda - Powiązania:
- https://bibliotekanauki.pl/articles/31339413.pdf
- Data publikacji:
- 2023
- Wydawca:
- Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Instytut Informatyki Technicznej
- Tematy:
-
image restoration
remote sensing images
artificial intelligence
AI
machine learning
ML
deep learning
DL
convolutional neural network
CNN - Opis:
- Remote sensing satellite images are affected by different types of degradation, which poses an obstacle for remote sensing researchers to ensure a continuous and trouble-free observation of our space. This degradation can reduce the quality of information and its effect on the reliability of remote sensing research. To overcome this phenomenon, the methods of detecting and eliminating this degradation are used, which are the subject of our study. The original aim of this paper is that it proposes a state of art of recent decade (2012-2022) on advances in remote sensing image restoration using machine and deep learning, identified by this survey, including the databases used, the different categories of degradation, as well as the corresponding methods. Machine learning and deep learning based strategies for remote sensing satellite image restoration are recommended to achieve satisfactory improvements.
- Źródło:
-
Machine Graphics & Vision; 2023, 32, 2; 147-167
1230-0535
2720-250X - Pojawia się w:
- Machine Graphics & Vision
- Dostawca treści:
- Biblioteka Nauki
Artykuł