TU4.M1.4
SS-CFPNet: SAR Image Despeckling for SAR Images Based on Centred Image Feature Pyramids
Yiheng Zhou, Bing Sun, Mingqing Han, Yihang Zhi, Beihang University, China
Session:
TU4.M1: SAR Image Restoration and Deep Learning: The Added Value of Artificial Intelligence in Handling Noise in Different SAR Image Configurations Oral
Track:
Community-Contributed Sessions
Location:
Room M1
Presentation Time:
Tuesday, 5 August, 16:30 - 16:45
Session Co-Chairs:
Giampaolo Ferraioli, Università degli Studi di Napoli Parthenope and Sergio Vitale, University of Naples Parthenope
Presentation
Discussion
Resources
No resources available.
Session TU4.M1
TU4.M1.1: SAR IMAGE RESTORATION: EXPLORING SIMILARITIES AND COMPLEMENTARITIES OF SUPERVISED AND SELF-SUPERVISED APPROACHES
Francescopaolo Sica, University of the Bundeswehr Munich, Germany
TU4.M1.2: A SELF-SUPERVISED ITERATIVE CONVOLUTIONAL NEURAL NETWORK FOR SAR IMAGE DESPECKLING
Lingdong Geng, Shuai Wang, Hongliang Lu, Xiping Yue, Wenjian Sun, Jili Sun, Qilu Aerospace Information Research Institute, China
TU4.M1.3: INCLUDING SAR ASSESSING METRICS IN DESPECKLING NETWORKS
Sergio Vitale, Giampaolo Ferraioli, Vito Pascazio, Università degli Studi di Napoli Parthenope, Italy; Luis Gomez Deniz, Universidad de Las Palmas de Gran Canaria, Spain
TU4.M1.4: SS-CFPNet: SAR Image Despeckling for SAR Images Based on Centred Image Feature Pyramids
Yiheng Zhou, Bing Sun, Mingqing Han, Yihang Zhi, Beihang University, China
TU4.M1.5: DEEP LEARNING FOR ENHANCING SENTINEL-1 IMAGERY
Juan Francisco Amieva, Christian Ayala, Tracasa Instrumental S.L., Spain; Mikel Galar, Universidad Pública de Navarra, Spain
Resources
No resources available.