Automatic UAV image registration using feature detection and matching with satellite imagery
Name
1080935038-MIT.pdf
Description
Full printable version
Size
16.37 MB
Format
Adobe PDF
Checksum (MD5)
47361d97a86b594bcf1abe62075882dc
Author(s)
Lucier, Jordan W
Advisor(s)
Hari Balakrishnan and Samuel Madden.
Alternative Title
Automatic unmanned aerial vehicle image registration using feature detection and matching with satellite imagery
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
This thesis presents an approach and implementation for using satellite imagery to perform image registration with unprocessed aerial images captured with a UAV. Aerial imagery is used in a large variety of applications including disaster relief, urban planning, crop and vegetation monitoring, and mapping. The common difficulty in utilizing aerial imagery captured by aircraft rather than satellite is that of image registration: transforming data into the image coordinate system. Often, the goal of these applications involves transforming location data into the image coordinate system for object extraction and further processing. Current approaches require hand-labeling of correspondences, the use of ground control points (GCPs), or human analysis to identify objects or locations of interest in the aerial imagery. As such, these methods do not sufficiently scale, generalize, or provide the efficiency required for these applications. The proposed approach to image registration in aerial imagery makes use of raw images captured on consumer-grade UAVs, and uses automatic feature detection and matching to register the imagery. This implementation provides a proof of concept, which was found to succeed on roughly 65% of our images.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 45-46).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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