Research on Image Super-Resolution Reconstruction Technology Based on Unsupervised Learning
Affected by the movement of drones, missiles, and other aircraft platforms and the limitation of the accuracy of image sensors, the obtained images have low-resolution and serious loss of image details. Aiming at these problems, this paper studies the image super-resolution reconstruction technology...
Saved in:
Published in | International Journal of Aerospace Engineering Vol. 2023; pp. 1 - 12 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Hindawi
21.11.2023
John Wiley & Sons, Inc Hindawi Limited Wiley |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Affected by the movement of drones, missiles, and other aircraft platforms and the limitation of the accuracy of image sensors, the obtained images have low-resolution and serious loss of image details. Aiming at these problems, this paper studies the image super-resolution reconstruction technology. Firstly, a natural image degradation model based on a generative adversarial network is designed to learn the degradation relationship between image blocks within the image; then, an unsupervised learning residual network is designed based on the idea of image self-similarity to complete image super-resolution reconstruction. The experimental results show that the unsupervised super-resolution reconstruction algorithm is equivalent to the mainstream supervised learning algorithm under ideal conditions. Compared to mainstream algorithms, this algorithm has significantly improved its various indicators in real-world environments under nonideal conditions. |
---|---|
ISSN: | 1687-5966 1687-5974 |
DOI: | 10.1155/2023/8860842 |