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Real imagery and video data from cameras are frequently needed to conduct research and experiments for model development, algorithm training, and more. When collecting real imagery and video with cameras in uncontrolled environments, the environmental signatures can change over time, like temperature and sun angles, and cause the image quality to change in an unpredictable and undesirable manner. Due to the limited availability of military targets, range availability, vast personnel support needed, and the typical high costs associated with conducting data collections in the field, it is imperative that low quality data is not unintentionally collected. Moreover, a need exists to increase automation in order to reduce manpower needed during data collections. To address such issues, this paper describes a software utility incorporating various image quality metrics (IQMs), which can enable automatic monitoring of the quality of collected imagery and video data with less cost and minimal modification of the imaging system. As a part of the utility, an automated alert algorithm based on a majority vote is discussed along with a selection of suitable IQMs according to their characteristics and temporal noise filtering for stable decision making. Design criteria for an optimal performance of the automated alert algorithm is presented. Also discussed is a practical application scenario that demonstrates the capabilities and limitations of the alert system using both real and synthetic video examples.
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