TY - JOUR
T1 - Deep-Learning-Based Zero-Sample Gradient Guidance Spatial Resolution Enhancement for Microwave Radiometer in Fengyun-3D
AU - Feng, Minghao
AU - Hu, Weidong
AU - Bai, Yuming
AU - Yao, Zhiyu
AU - Rastinasab, Vahid
AU - Shang, Jian
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - For satellite brightness temperature images, researchers are constantly pursuing higher resolutions to obtain more detailed meteorological information. In this article, a novel deep-learning-based modeling approach, named zero-sample gradient guidance spatial resolution enhancement (ZSGRE), is developed explicitly for microwave radiometers. The detailed model, including mathematical derivation and key parameters, is presented. Subsequently, the proposed approach is applied in four scenarios: synthetic scene, simulated geographical brightness temperature, practical measurement of microwave radiometer in Fengyun-3D (FY-3D), and a cyclone analysis on the Atlantic. Compared with other methods, the proposed ZSGRE method improves 2.51% of structural similarity (SSIM), enhances 2.3 dB of peak signal-to-noise ratio (PSNR), and decreases 15.8% of instantaneous field of view (IFOV). Such applications demonstrate ZSGRE’s significant performance: zero-sample preparation and spatial resolution enhancement.
AB - For satellite brightness temperature images, researchers are constantly pursuing higher resolutions to obtain more detailed meteorological information. In this article, a novel deep-learning-based modeling approach, named zero-sample gradient guidance spatial resolution enhancement (ZSGRE), is developed explicitly for microwave radiometers. The detailed model, including mathematical derivation and key parameters, is presented. Subsequently, the proposed approach is applied in four scenarios: synthetic scene, simulated geographical brightness temperature, practical measurement of microwave radiometer in Fengyun-3D (FY-3D), and a cyclone analysis on the Atlantic. Compared with other methods, the proposed ZSGRE method improves 2.51% of structural similarity (SSIM), enhances 2.3 dB of peak signal-to-noise ratio (PSNR), and decreases 15.8% of instantaneous field of view (IFOV). Such applications demonstrate ZSGRE’s significant performance: zero-sample preparation and spatial resolution enhancement.
KW - Fengyun-3D (FY-3D)
KW - microwave radiometer
KW - spatial resolution enhancement
KW - zero sample
UR - http://www.scopus.com/inward/record.url?scp=105003779327&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2025.3560553
DO - 10.1109/TGRS.2025.3560553
M3 - Article
AN - SCOPUS:105003779327
SN - 0196-2892
VL - 63
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
M1 - 5301311
ER -