Abstract
The head-up display (HUD) projects a virtual image in the driver’s field of vision. Here, the image quality plays an important role. However, assembly tolerances cause image distortions. The evaluation of these distortions is a current issue, because procedures for the assessment of optical aberrations cannot be applied. Therefore new features and methods are implemented, which evaluate the subjective impression of distortions. The overall objective is to investigate the correlation between subjective labels and objective features. A total of 13 features are required to describe the image quality. Subsequently, the relationship between the labels and the features is adapted to a regression equation. For it, representative images are needed, which are selected by cluster analytical methods.
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Köppl, S., Hellmann, M., Jostschulte, K., Wöhler, C. (2016). Evaluation of the Individually Perceived Quality from Head-Up Display Images Relating to Distortions. In: Wilhelm, A., Kestler, H. (eds) Analysis of Large and Complex Data. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-25226-1_23
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DOI: https://doi.org/10.1007/978-3-319-25226-1_23
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