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The human visual sense is superior to today’s computers in terms of perceiving image content. Using the human visual system's high bandwidth supports rapid transfer of digital data representations to the user. It is this human capability that visualization builds upon, by generating images representing the content of large and complex data sets. In image science, the goal is to translate complex spatio-temporal patterns into forms that can be interpreted by humans. Thus, through a series of processing steps information can be extracted from the objects embedded images or volumetric datasets. In some senses this can be seen as the opposite of the image synthesis taking place in visualization.
Interactivity plays a central role in visualization and image science workflows, as the user needs to feed back gained insights and steer the capturing, filtering and refining steps to reach the goal of detecting expected features and discovering unexpected ones in the plentitude of data.
Here are some examples of our research: