Abstract
Deconvolution is widely used to improve resolution in microscopy. Unfortunately, deconvolution in optical coherence tomography (OCT) is sensitive to noise which inherently results in additive artifacts. These artifacts severely impair the fidelity of deconvolved images and limit its use in OCT imaging. Here we propose a framework that encodes numerical random phase masks in the Fourier space of a deconvolved OCT image, to produce a sub-resolution image with the artifacts removed. The optimized joint operation of an iterative Richardson-Lucy deconvolution and a numerical synthesis of random phase masks (RPM), termed as Deconv-RPM, enables a 2.7-fold enhancement in both transverse and axial resolutions. We demonstrate that the Deconv-RPM method allows imaging previously unresolved cellular-level details in the human labial mucosa in vivo with significantly improved clarity.
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