Back to articles
Articles
Volume: 31 | Article ID: art00002
Abstract

Image quality (IQ) metrics are used to assess the quality of a detected image under a specified set of capture and display conditions. A large volume of work on IQ metrics has considered the quality of the image from an aesthetic point of view — visual perception and appreciation of the final result. Metrics have also been developed for “informational” applications such as medical imaging, aerospace and military systems, scientific imaging and industrial imaging. In these applications the criteria for image quality are based on information content and the ability to detect, identify and recognize objects from a captured image. Development of automotive imaging systems requires IQ metrics that are useful in automotive imaging. Many of the metrics developed for informational imaging are also potentially useful in automotive imaging, since many of the tasks — for example object detection and identification — are similar. In this paper, we review the Signal to Noise Ratio of the Ideal Observer and present it as a useful metric for determining whether an object can be detected with confidence, given the characteristics of an automotive imaging system. We also show how this metric can be used to optimize system parameters for a defined task.

Subject Areas :
Views 121
Downloads 34
 articleview.views 121
 articleview.downloads 34
  Cite this article 

Paul J. Kane, "Signal detection theory and automotive imagingin Proc. IS&T Int’l. Symp. on Electronic Imaging: Autonomous Vehicles and Machines Conference,  2019,  pp 27-1 - 27-8,  https://doi.org/10.2352/ISSN.2470-1173.2019.15.AVM-027

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2019
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA