We present a half-day tutorial to review different applications of information theory to visualization. Information theory tools, widely used in scientific fields such as engineering, physics, genetics, neuroscience, and more recently in computer graphics, are also emerging as state of the art in visualization.

Applications areas are view selection, flow visualization, ambient occlusion, time-varying volume visualization, transfer function definition, LOD timevarying volume visualization, iso-surface similarity maps and quality metrics.

The applications fall broadly into two categories: the mapping of the problem to an information channel, as in viewpoint applications, and the direct use of measures as entropy, Kullback-Leibler distance, Jensen-Shannon divergence, and f-divergences, to evaluate for instance the homogeneity of a set of samples or being used as metrics. We will also discuss the potential applications of information bottleneck method that allows us to progressively extract or merge information in a hierarchical structure.