Extraction of the lateral resolution in a plenoptic camera using the SPC model

Established capturing properties like image resolution need to be described thoroughly in complex multidimensional capturing setups such as plenoptic cameras (PC), as these introduce a trade-off between resolution and features such as field of view, depth of field, and signal to noise ratio. Models, methods and metrics that assist exploring and formulating this trade-off are highly beneficial for study as well as design of complex capturing systems. This work presents how the important high-level property lateral resolution is extracted from our previously proposed Sampling Pattern Cube (SPC) model. The SPC carries ray information as well as focal properties of the capturing system it models. The proposed operator extracts the lateral resolution from the SPC model throughout an arbitrary number of depth planes resulting in a depth-resolution profile. We have validated the resolution operator by comparing the achieved lateral resolution with previous results from more simple models and from wave optics based Monte Carlo simulations. The lateral resolution predicted by the SPC model agrees with the results from wave optics based numerical simulations and strengthens the conclusion that the SPC fills the gap between ray-based models and wave optics based models, by including the focal information of the system as a model parameter. The SPC is proven a simple yet efficient model for extracting the depth-based lateral resolution as a high-level property of complex plenoptic capturing system.