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Quality Assessment of SAR-to-Optical Image Translation
Content Provider | MDPI |
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Author | Zhang, Jiexin Zhou, Jianjiang Li, Minglei Zhou, Huiyu Yu, Tianzhu |
Copyright Year | 2020 |
Description | Synthetic aperture radar (SAR) images contain severe speckle noise and weak texture, which are unsuitable for visual interpretation. Many studies have been undertaken so far toward exploring the use of SAR-to-optical image translation to obtain near optical representations. However, how to evaluate the translation quality is a challenge. In this paper, we combine image quality assessment (IQA) with SAR-to-optical image translation to pursue a suitable evaluation approach. Firstly, several machine-learning baselines for SAR-to-optical image translation are established and evaluated. Then, extensive comparisons of perceptual IQA models are performed in terms of their use as objective functions for the optimization of image restoration. In order to study feature extraction of the images translated from SAR to optical modes, an application in scene classification is presented. Finally, the attributes of the translated image representations are evaluated using visual inspection and the proposed IQA methods. |
Starting Page | 3472 |
e-ISSN | 20724292 |
DOI | 10.3390/rs12213472 |
Journal | Remote Sensing |
Issue Number | 21 |
Volume Number | 12 |
Language | English |
Publisher | MDPI |
Publisher Date | 2020-10-22 |
Access Restriction | Open |
Subject Keyword | Remote Sensing Imaging Science Synthetic Aperture Radar (sar) Generative Adversarial Networks (gans) Sar-to-optical Image Translation Image Quality Assessment (iqa) Image Restoration |
Content Type | Text |
Resource Type | Article |