Assessing the 3D resolution of refocused correlation plenoptic images using a general-purpose image quality estimator

Abstract

Correlation plenoptic imaging (CPI) is emerging as a promising approach to light-field imaging (LFI), a technique enabling simultaneous measurement of light intensity distribution and propagation direction from a scene. LFI allows single-shot 3D sampling, offering fast 3D reconstruction for a wide range of applications. However, the array of micro-lenses typically used in LFI to obtain 3D information limits image resolution, which rapidly declines with enhanced volumetric reconstruction capabilities. CPI addresses this limitation by decoupling the measurement of the light field on two photodetectors with spatial resolution, eliminating the need for micro-lenses. 3D information is encoded in a four-dimensional correlation function, which is decoded in post-processing to reconstruct images without the resolution loss seen in conventional LFI. This paper evaluates the tomographic performance of CPI, demonstrating that the refocusing reconstruction method provides axial sectioning capabilities comparable to conventional imaging systems. A general-purpose analytical approach based on image fidelity is proposed to quantitatively study axial and lateral resolution. The analysis fully characterizes the volumetric resolution of any CPI architecture, offering a comprehensive evaluation of its imaging performance.