Digital cameras are increasingly used in automotive applications. As these cameras are integrated into active safety systems, image quality becomes ever more important. The captured image information is limited not only by the sensitivity and signal-to-noise ratio of the image sensor, but also by such image capture conditions as ambient lighting, camera-object distance, and relative camera-object velocity. For example, the detection of a pedestrian at night might be further impeded by the headlights of oncoming traffic. Image quality performance characterizes the ability of the imaging system to capture vital image information under application-typical capture conditions. Characterizing objective image quality performance requires clearly defined image quality attributes and metrics. This paper introduces the basic concepts of objective and subjective image quality, reviews existing image quality metrics and standards that have been developed for digital still and video applications, and explores their applicability for automotive uses where image information is interpreted by a human observer or machine vision application. The automotive photospace is introduced as a useful tool to characterize the automotive image capture conditions, and distinguish them from other still and video applications. As automotive imaging becomes more widespread, early standardization of image quality is important. This will enable automotive camera suppliers and the automotive industry to communicate in a common language when specifying imaging systems so that sufficient image quality under application conditions is ensured.
Image Quality Standards in Automotive Vision Applications
2007 IEEE Intelligent Vehicles Symposium ; 404-409
2007-06-01
1088437 byte
Conference paper
Electronic Resource
English
Image Quality Standards in Automotive Vision Applications
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