WEP.P10.4

ONLINE SPARSE SUPER-RESOLUTION METHOD FOR RADAR FORWARD-LOOKING IMAGING USING MAJORIZE-MINIMIZATION

Xichen Yin, Yulin Huang, Yongchao Zhang, Yongwei Zhang, Xingyu Tuo, Yin Zhang, Jianyu Yang, University of Electronic Science and Technology of China, China
Session:
WEP.P10: Super Resolution and Reconstruction Poster
Track:
Data Analysis
Location:
Poster Area 10
Presentation Time:
Wed, 19 Jul, 14:15 - 15:45 Pacific Time (UTC -8)
Session Chair:
Joan Francesc Munoz-Martin, Jet Propulsion Laboratory / California Institute of Technology
Session Managers:
Ge Jiang and HUMAIRA SANAM and Ayoti Banerjee and Srashti Singh
Presentation
Not logged in.
Discussion
Not logged in.
Resources
No resources available.
Session WEP.P10
WEP.P10.1: TWO-DIMENSIONAL SUPER-RESOLUTION IMAGING FOR SCANNING RADAR USING SPARSE LEARNING VIA ITERATIVE MINIMIZATION
Jiawei Luo, Yongchao Zhang, Deqing Mao, Yin Zhang, Yulin Huang, Jianyu Yang, University of Electronic Science and Technology of China, China
WEP.P10.2: ADAPTIVE SPARSE ITERATIVE REWEIGTHED SUPER-RESOLUTION METHOD FOR SCANNING RADAR IMAGING
Yongwei Zhang, Jiawei Luo, Yongchao Zhang, Lihua Ren, Yin Zhang, Yulin Huang, Jianyu Yang, University of Electronic Science and Technology of China, China
WEP.P10.3: TWO-DIMENSIONAL FAST SUPERRESOLUTION IMAGING FOR REAL APERTURE RADAR UNDER NON-UNIFORM SAMPLING MODEL
Jianan Yan, Yongchao Zhang, Shuaidi Liu, Jiawei Luo, wei pu, Jianyu Yang, University of Electronic Science and Technology of China, China
WEP.P10.4: ONLINE SPARSE SUPER-RESOLUTION METHOD FOR RADAR FORWARD-LOOKING IMAGING USING MAJORIZE-MINIMIZATION
Xichen Yin, Yulin Huang, Yongchao Zhang, Yongwei Zhang, Xingyu Tuo, Yin Zhang, Jianyu Yang, University of Electronic Science and Technology of China, China
WEP.P10.5: A SPLIT ITERATIVE ADAPTIVE APPROACH FOR SUPER-RESOLUTION IMAGING OF SPARSE SCENE
Shuaidi Liu, Yongchao Zhang, Jiawei Luo, Wenjing Wang, Yulin Huang, Jianyu Yang, University of Electronic Science and Technology of China, China
WEP.P10.6: AN IMPROVED DUAL POLARIMETRIC SAR QUAD-POL IMAGE RECONSTRUCTION METHOD BASED ON FULL CONVOLUTIONAL END-TO-END NEURAL NETWORK
Jun-Wu Deng, Ming-Dian Li, Xing-Chao Cui, Si-Wei Chen, National University of Defense Technology, China
WEP.P10.7: IMAGE RECONSTRUCTION FOR LOW-OVERSAMPLED STAGGERED SAR BASED ON BAYESIAN COMPRESSIVE SENSING
Wenjiao Chen, Space Engineering University, China; Li Zhang, The 15th Research Institute of China Electronics Technology Corporation, China; Jiwen Geng, Southeast University, China; Honglin Liu, Space Engineering University, China
WEP.P10.8: OPTIMAL PARAMETER ESTIMATION OF BSDF IN SAR SIMULATION BASED ON DIFFERENTIAL RAY TRACING
Jiangtao Wei, Feng Xu, Fengming Hu, Fudan University, China
WEP.P10.9: ESTIMATION OF SIGNIFICANT WAVE HEIGHT FROM GAOFEN-3 SAR WAVE MODE DATA BASED ON ELASTIC NET REGRESSION
Qiushuang Yan, Tianran Song, China University of Petroleum (huadong), China; Chenqing Fan, First Institute of Oceanography, Ministry of Natural Resources, China; Jie Zhang, China University of Petroleum (huadong), China
WEP.P10.10: A REVISED TWO-LEAF LIGHT USE EFFICIENCY MODEL FOR IMPROVING GROSS PRIMARY PRODUCTION ESTIMATION AT A TROPICAL EVERGREEN BROADLEAVED FOREST SITE
Lingxiao Huang, Chinese Academy of Sciences, China; Meng Liu, Chinese Academy of Agricultural Sciences, China; Yazhen Jiang, Ronglin Tang, Chinese Academy of Sciences, China
WEP.P10.11: ESTIMATION OF LEAF AREA INDEX FROM VIIRS SURFACE REFLECTANCE BASED ON DEEP TRANSFER LEARNING
Li Juan, Xiao Zhiqiang, Hong Tang, beijing normal university, China
WEP.P10.12: COMPARISONS OF THREE SINGLE-CHANNEL ALGORITHMS FOR RETRIEVING LAND SURFACE TEMPERATURE FROM HJ-1B SATELLITE DATA
Guoqin Zhang, Dacheng Li, Taiyuan University of Technology, China; Hua Li, State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, China; Fan Mo, Institute of Remote Sensing Satellite,China Academy of Space Technology, China; Yi Yang, Hui Jia, Jie Yu, Yue Lyu, Taiyuan University of Technology, China
Resources
No resources available.