FPGA system for real-time computational extended depth of field imaging using phase aperture coding
This addresses the challenge of real-time imaging with extended depth of field for applications like microscopy or photography, though it appears incremental as it builds on existing computational imaging concepts.
The researchers tackled the problem of real-time computational extended depth of field imaging by developing a system using a phase-coded aperture and a fast non-iterative reconstruction algorithm, achieving real-time performance on an FPGA with output qualitatively and quantitatively better than state-of-the-art blind deblurring.
We present a proof-of-concept end-to-end system for computational extended depth of field (EDOF) imaging. The acquisition is performed through a phase-coded aperture implemented by placing a thin wavelength-dependent optical mask inside the pupil of a conventional camera lens, as a result of which, each color channel is focused at a different depth. The reconstruction process receives the raw Bayer image as the input, and performs blind estimation of the output color image in focus at an extended range of depths using a patch-wise sparse prior. We present a fast non-iterative reconstruction algorithm operating with constant latency in fixed-point arithmetics and achieving real-time performance in a prototype FPGA implementation. The output of the system, on simulated and real-life scenes, is qualitatively and quantitatively better than the result of clear-aperture imaging followed by state-of-the-art blind deblurring.