Karin Griffis

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In this work, we propose an algorithm for the automatic, qualitative explanation of object-level changes in multispectral remote sensing imagery. This multi-stage approach is based on the construction of change models that directly reflect the nuisance effects of the data acquisition process, unimportant causes of observed object variation, such as(More)
Automated data interpretation and change detection algorithms are useful aids in the handling of the vast arrays of data collected by remote spacebourne sensors. The automatic interpretation of detected changes between images enables meaningful semantic descriptions which can be used for applications such as ecological system monitoring and surveillance [1,(More)
Many video codecs rely on a periodically embedded codes to maintain synchronization. In order to increase system robustness, we propose a detection algorithm to determine synchronization code location. The associated metric relies on knowledge of the distribution of the locations of codes within the compressed data. These distributions are modeled as(More)
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