Event Details
Deep Learning in Synthetic Aperture Radar
Presenter: Khaled Kelany
Supervisor:
Date: Tue, August 3, 2021
Time: 11:00:00 - 00:00:00
Place: ZOOM - Please see below.
ABSTRACT
Link: https://uvic.zoom.us/j/87997357500?pwd=MGRFdWI2ZnZwUllaNHBtekUzVWNxdz09
Meeting ID: 879 9735 7500
Password: 761281
Note: Please log in to Zoom via SSO and your UVic Netlink ID
Abstract: Mapping of earth resources, environmental monitoring, and many other systems require high-resolution wide-area imaging. Such images often have to be captured at night or in inclement weather conditions, a capability is provided by Synthetic Aperture Radar (SAR). SAR systems exploit radar signal’s long-range propagation and utilize digital electronics to process complex information, all of which enables high-resolution imagery. This gives SAR systems advantages over optical imaging systems, since, unlike optical imaging, SAR is effective at any time of day and in any weather conditions. Moreover, an advanced technology called Interferometric Synthetic Aperture Radar (InSAR) has the potential to apply phase information from SAR images and to measure ground surface deformation. However, given the current state of technology, the quality of InSAR data can be distorted by several factors, such as image co-registration, interferogram generation, phase unwrapping, and geocoding.
Image co-registration aligns two or more images so that the same pixel in each image corresponds to the same point of the target scene. Super-Resolution (SR), on the other hand, is the process of generating high-resolution (HR) images from a low-resolution (LR) one. SR influences the co-registration quality and therefore could potentially be used to enhance later stages of SAR images processing. Our study achieved two major contributions towards the enhancement of SAR processing. The first one is devising a new learning-based SR model that can be applied with SAR, and similar applications. A second major contribution is utilizing the devised model for improving SAR co-registration and InSAR interferogram generation, together with methods for evaluating the quality of the resulting images.