Bio-Inspired Computational Imaging: Components, Algorithms, and Systems.

Abstract

Artificial vision has advanced significantly on the basis of insights from human and animal vision. Still, biological vision retains advantages over mainstream computer vision, notably in terms of robustness, adaptability, power consumption, and compactness. Natural vision also demonstrates a great diversity of solutions to problems, adapted to specific tasks. Biological vision best corresponds to the subfield of computation imaging, in which optics and algorithms are codesigned to uncover scene information. We review current progress and opportunities in optics, sensors, algorithms, and joint designs that enable computational cameras to mimic the power of natural vision.