Authors:
(1) Hyosun park, Department of Astronomy, Yonsei University, Seoul, Republic of Korea;
(2) Yongsik Jo, Artificial Intelligence Graduate School, UNIST, Ulsan, Republic of Korea;
(3) Seokun Kang, Artificial Intelligence Graduate School, UNIST, Ulsan, Republic of Korea;
(4) Taehwan Kim, Artificial Intelligence Graduate School, UNIST, Ulsan, Republic of Korea;
(5) M. James Jee, Department of Astronomy, Yonsei University, Seoul, Republic of Korea and Department of Physics and Astronomy, University of California, Davis, CA, USA.
Table of Links
2 Method
2.1. Overview and 2.2. Encoder-Decoder Architecture
2.3. Transformers for Image Restoration
4 JWST Test Dataset Results and 4.1. PSNR and SSIM
4.3. Restoration of Morphological Parameters
4.4. Restoration of Photometric Parameters
5.2. Restoration of Multi-epoch HST Images and Comparison with Multi-epoch JWST Images
6 Limitations
6.1. Degradation in Restoration Quality Due to High Noise Level
6.2. Point Source Recovery Test
6.3. Artifacts Due to Pixel Correlation
7 Conclusions and Acknowledgements
Appendix: A. Image restoration test with Blank Noise-Only Images
6.3. Artifacts Due to Pixel Correlation
In our generation of LQ images, we assume that the noise is Gaussian. However, in real astronomical images, especially when we create deep images by stacking many dithered exposures, there exist significant interpixel noise correlations. We find that these inter-pixel noise correlations create non-negligible artifacts.
Figure 13 display some examples of these artifacts. The LQ images here are sampled from multi-epoch drizzled images. The presence of correlated noise is apparent
even from visual inspection. The RS images show that the correlated noise creates some low-surface brightness artifacts in the galaxy outskirts, which however are absent in the JWST images. Addressing this issue could involve strategies such as employing a different drizzling kernel for image stacking or leveraging more advanced deep learning algorithms. Exploring these solutions will be a key focus of our future work.
This paper is available on arxiv under CC BY 4.0 Deed license.
