Comparative analysis of signal-to-noise ratio in correlation plenoptic imaging architectures

Abstract

Correlation plenoptic imaging (CPI) is a scanning-free diffraction-limited 3D optical imaging technique exploiting the peculiar properties of correlated light sources. CPI has been further extended to samples of interest to microscopy, such as fluorescent or scattering objects, in a modified architecture named correlation light-field microscopy (CLM). Interestingly, experiments have shown that the noise performances of CLM are significantly improved over the original CPI scheme, leading to better images and faster acquisition. In this work, we provide a theoretical foundation to such advantage by investigating the properties of both the signal-to-noise and the signal-to-background ratios of CLM and the original CPI setup.

Correlated-photon imaging at 10 volumetric images per second

“…First, if camera frames are required, the total acquisition time is equal to , with R the frame rate; its inverse is the rate at which correlation images can be acquired. The acquisition rate can be reduced by i) maximizing R , as in high-speed sensors, and ii) optimizing the trade-off between number of frames and SNR, with the latter expected to depend on 18 , 40 – 43 . The other crucial time scale to be considered is the gating time , namely, the effective sensitivity window in which a single frame is acquired: if it is larger than the source coherence time, intensity fluctuations in each frame are partially erased 44 , making it more difficult to reconstruct their correlations, and thus increasing the required .…”

Compressive sensing-based correlation plenoptic imaging

“…Despite their promising application potentials, CPI and GI share the main drawback of correlation imaging techniques, namely, the need to accumulate statistics (i.e., independent intensity frames) in order to reconstruct the desired correlation signal. In particular, the signal-to-noise ratio (SNR) of CPI and GI images scales like the square root of the number of acquired frames [27][28][29], but the acquisition time increases linearly in the latter quantity, leading to a necessary compromise between accurate and fast imaging. In the case of GI, many efforts have been made to reduce the sampling rate and enhance the acquisition speed without sacrificing the image quality.…”