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Open Access Signal detection theory and automotive imaging

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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.
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Keywords: Automotive imaging; Detection probability; Ideal Observer; Noise equivalent quanta; Object detection; image quality

Document Type: Research Article

Publication date: January 13, 2019

This article was made available online on January 13, 2019 as a Fast Track article with title: "Signal detection theory and automotive imaging".

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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