Automated noise estimation in polarization-sensitive optical coherence tomography

Advanced signal reconstruction in polarization-sensitive optical coherence tomography (OCT) frequently relies on an accurate determination of the signal noise floor. However, current methods for evaluating the noise floor are often impractical and subjective. Here we present a method using the degree of polarization uniformity and known speckle intensity statistics to model and estimate the OCT noise floor automatically. We establish the working principle of our method with a series of phantom experiments and demonstrate the robustness of our noise estimation method across different imaging systems and applications in vivo.