  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 light-field information measurement using 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. This analysis fully
characterizes the volumetric resolution of any CPI architecture, offering a
comprehensive evaluation of its imaging performance.
