Exploring and exploiting the physical- and information-theoretical limits for better Computational 3D Imaging
Computational 3D imaging and 3D display principles are ‘enabling technologies’ that have the potential to foster transformational technical changes in the next decades. The list of possible future applications scenarios is long. In midst of seemingly endless possibilities, however, the knowledge about fundamental physical and information-theoretical limits in imaging proves to be a powerful tool: By knowing that our imaging device already operates at the physical limit (e.g., of resolution), we can avoid unnecessary effort and investments in better hardware such as faster detectors, or cameras with higher pixel resolution. Moreover, limits often appear as uncertainty products, making it possible to optimize our system towards a specific quantity (e.g., speed) by trading in information less critical for the respective application. Although the imaging device is essential in this optimization, the central role is assumed by the illumination, which serves as encoder of the desired information.
This special information-driven way to think about computational imaging systems has a long tradition at the Erlangen Institute of Optics, Information and Photonics, and was decisively shaped by Prof. Willomitzer’s former PhD advisor Prof. Gerd Häusler. This research track is a continuation of this long-standing tradition. Please also visit Gerd Häusler’s website for more information.
