Affordable Access

deepdyve-link
Publisher Website

Remote classification from an airborne camera using image super-resolution.

Authors
  • Woods, Matthew
  • Katsaggelos, Aggelos
Type
Published Article
Journal
Journal of the Optical Society of America A
Publisher
The Optical Society
Publication Date
Feb 01, 2017
Volume
34
Issue
2
Pages
203–215
Identifiers
DOI: 10.1364/JOSAA.34.000203
PMID: 28157846
Source
Medline
License
Unknown

Abstract

The image processing technique known as super-resolution (SR), which attempts to increase the effective pixel sampling density of a digital imager, has gained rapid popularity over the last decade. The majority of literature focuses on its ability to provide results that are visually pleasing to a human observer. In this paper, we instead examine the ability of SR to improve the resolution-critical capability of an imaging system to perform a classification task from a remote location, specifically from an airborne camera. In order to focus the scope of the study, we address and quantify results for the narrow case of text classification. However, we expect the results generalize to a large set of related, remote classification tasks. We generate theoretical results through simulation, which are corroborated by experiments with a camera mounted on a DJI Phantom 3 quadcopter.

Report this publication

Statistics

Seen <100 times