1 code implementation • 27 Jan 2020 • Subhayan Mukherjee, Aaron Zimmer, Xinyao Sun, Parwant Ghuman, Irene Cheng
GenInSAR's Phase, and Coherence Root-Mean-Squared-Error and Phase Cosine Error have average improvements of 0. 54, 0. 07, and 0. 05 respectively compared to the related methods.
1 code implementation • 20 Jan 2020 • Subhayan Mukherjee, Aaron Zimmer, Navaneeth Kamballur Kottayil, Xinyao Sun, Parwant Ghuman, Irene Cheng
Interferometric Synthetic Aperture Radar (InSAR) imagery for estimating ground movement, based on microwaves reflected off ground targets is gaining increasing importance in remote sensing.
1 code implementation • 20 Jan 2020 • Subhayan Mukherjee, Aaron Zimmer, Xinyao Sun, Parwant Ghuman, Irene Cheng
Interferometric Synthetic Aperture Radar (InSAR) imagery based on microwaves reflected off ground targets is becoming increasingly important in remote sensing for ground movement estimation.
1 code implementation • 20 Jan 2020 • Subhayan Mukherjee, Navaneeth Kamballur Kottayil, Xinyao Sun, Irene Cheng
We propose a novel direction to improve the denoising quality of filtering-based denoising algorithms in real time by predicting the best filter parameter value using a Convolutional Neural Network (CNN).
1 code implementation • 6 Sep 2019 • Xinyao Sun, Aaron Zimmer, Subhayan Mukherjee, Navaneeth Kamballur Kottayil, Parwant Ghuman, Irene Cheng
In this work, we propose a deep convolutional neural network (CNN) based model DeepInSAR to intelligently solve both the phase filtering and coherence estimation problems.