Bayes' theorem-based binary algorithm for fast reference-less calibration of a multimode fiber.

In this paper, we present a Bayes' theorem-based high-speed algorithm, to measure the binary transmission matrix of a multimode fiber using a digital micromirror device, in a reference-less multimode fiber imaging system. Based on conditional probability, we define a preset threshold to locate those digital-micromirror-device pixels that can be switched 'ON' to form a focused spot at the output. This leads to a binary transmission matrix consisting of '0' and '1' elements. High-enhancement-factor light focusing and raster-scanning at the distal end of the fiber are demonstrated experimentally. The key advantage of our algorithm is its capability for fast calibration of a MMF to form a tightly focused spot. In our experiment, for 5000 input-output pairs, we only need 0.26 s to calibrate one row of the transmission matrix to achieve a focused spot with an enhancement factor of 28. This is more than 10 times faster than the prVBEM algorithm. The proposed Bayes' theorem-based binary algorithm can be applied not only in multimode optical fiber focusing but also to other disordered media. Particularly, it will be valuable in fast multimode fiber calibration for endoscopic imaging.