Sensitivity is a critical figure of merit to quantify measurement performance in quantitative phase imaging. It is affected by various noise sources in the system and by signal processing algorithms. Here we propose a three-level framework for sensitivity evaluation, including the Cramér-Rao bound (CRB), algorithmic sensitivity, and experimental sensitivity. Comparing the first two determines the theoretical efficiency of an algorithm, while inspecting the gap between the latter two reveals system efficiency. As an example, we apply this framework to wavelength shifting interferometry, an important category of quantitative phase imaging techniques. In a shot-noise-limited regime, the CRB is derived, and the performance of a four-step Carré algorithm is studied in simulations and experiments. Importantly, the proposed procedure allows the algorithmic sensitivity to be conveniently estimated from a single set of measurement data, which serves as a basis for system efficiency evaluation.
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Chen et al. (2017) studied this question.
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