Abstract

Local phase retardation (LPR) is increasingly recognized as a crucial biomarker for assessing disease progression. However, the presence of speckle noise significantly challenges its accuracy and polarization contrast. To address this challenge, we propose a signal-processing strategy aimed at reducing the impact of noise on LPR measurements. In this approach, the LPR is reconstructed by polar decomposition after averaging multiple Mueller matrices from different overlapping sub-spectra. To optimize measurement accuracy, we systematically combined and traversed different sub-spectral numbers and bandwidths. By examining the quarter-wave plate and glass slide, high-accuracy phase retardation measurements were successfully verified, and the maximum polarization contrast was improved by 23%. Moreover, experimental results from multi-tissue imaging vividly illustrate that the equivalent number of looks (ENL) and polarization contrast were improved by 18% and 19%, respectively. This outcome indicates that our proposed strategy can effectively reduce the noise spikes, enhancing tissue discrimination capabilities.

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