An Unsupervised Generative Neural Approach for InSAR Phase Filtering and Coherence Estimation

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.

CNN-based InSAR Denoising and Coherence Metric

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.

Image Denoising

CNN-based InSAR Coherence Classification

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.

Classification General Classification

CNN-Based Real-Time Parameter Tuning for Optimizing Denoising Filter Performance

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).

Denoising SSIM

DeepInSAR: A Deep Learning Framework for SAR Interferometric Phase Restoration and Coherence Estimation

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.

3D Plane Detection