Inverse problem approach in particle digital holography: out-of-field particle detection made possible.

We propose a microparticle detection scheme in digital holography. In our inverse problem approach, we estimate the optimal particles set that best models the observed hologram image. Such a method can deal with data that have missing pixels. By considering the camera as a truncated version of a wider sensor, it becomes possible to detect particles even out of the camera field of view. We tested the performance of our algorithm against simulated and experimental data for diluted particle conditions. With real data, our algorithm can detect particles far from the detector edges in a working area as large as 16 times the camera field of view. A study based on simulated data shows that, compared with classical methods, our algorithm greatly improves the precision of the estimated particle positions and radii. This precision does not depend on the particle's size or location (i.e., whether inside or outside the detector field of view).