Abstract
In an increasing number of cars, the driver is supported by Advanced Driver Assistance Systems (ADAS). In particular camera based ADAS are a key component for further improvements in safety and driving comfort. While imaging sensors are performing well under good weather conditions, their efficiency suffers under adverse environmental influences such as heavy rain, fog or snow. To handle such optical threats and to estimate information quality of cameras in order to warn the assistance system of possible critical working conditions, a self-diagnosis mechanism is of great importance for reliable operation of an optical ADAS.
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