Manual pavement condition surveys are gradually replaced by more comprehensive automated surveys conducted by multi-function highway evaluation vehicles. Digital imaging systems installed in automated highway evaluation vehicles are generally designed on modular basis where subsystems by different manufacturers are assembled to customize the system and fulfill the needs of users while minimizing the cost. Images acquired by digital cameras of the imaging subsystem can become contaminated by noise affecting their quality and the ability of identifying important pavement features. The first phase of the work involved research of basic criteria for evaluation of image quality through measurement of well-defined properties of images. The second phase of the research is focused on the investigation of the sources of noise that can affect the digital pavement distress images. As a result of this study, a novel technique was developed to filter out noise present in pavement distress image. The conclusions drawn from second phase can be used to minimize the effect of noise on digital images of pavement distress images.

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