Computational diffractive imagers employ special optical phase gratings integrated with photodetector matrices. Such imagers do not require a lens, and so can be extremely small and inexpensive. Captured interference patterns are unintelligible to a human observer, but the captured data includes sufficient information to allow the image or aspects of the image to be computed. Computational diffractive imagers can be tailored to extract application-specific information or compute decisions (rather than compute an image) based on the optical signal. Both the phase grating and the signal processing can be optimized for the information in the visual field and the task at hand. For example, sequences of interference patterns can be compared to measure changes in angular position, and this information can be used to sense and measure motion. Such interference patterns can also be used for pattern recognition, such as to perform automated face detection and recognition.
OPTICAL FLOW SENSING AND PATTERN RECOGNITION WITH ANTISYMMETRIC PHASE GRATINGS