Real-time phase retrieval in division of aperture microscopy with the transport of intensity equation.

The transport of intensity equation (TIE) allows to recover the phase of a microscopy sample from differently focused intensity measures along the axial direction of its optical field. In the present work, we propose a cost-effective technique for snapshot phase retrieval with TIE. The optics of a commercially available camera is replaced with a doublet system consisting of a microscope objective and a lenslet array with an extra lens mask attached to it. The system allows to obtain, in real-time and with no mechanical shift of either the sample or the sensor, the in-focus as well as a defocused image of the sample. From these two sub-aperture images, the intensity derivative term in TIE can then be approximated after image rectification. Phase is then retrieved for static as well as dynamic samples over the common view area. Validation experiments are presented.

Snapshot polarimetric imaging in multi-view microscopy.

Polarimetric imaging allows for the vector nature of optical information across a scene to be obtained, with recent applications ranging from remote sensing to microscopy. In polarimetric microscopy in particular, different polarization states are conventionally achieved under time-division multiplexing strategies and are mainly subject to static phenomena. In the present work, we propose a cost-effective technique for polarization sensing with the possibility of real-time imaging microscopy. By modifying a commercial camera and replacing the conventional lens with an optical system that integrates a microscope objective and a lenslet array with a polarization mask, linear Stokes parameters can be obtained in a snapshot. The proposed scheme is robust against misalignment and suitable for handling video sequences of microscopic samples. To the best of our knowledge, this is the first report on combining multi-view sensing and polarization imaging for applications to microscopy.

Fully invariant generalized Hough transform by out-of-focus multiview sensing with pupil array.

Recognition of geometrical shapes in real-time and fully invariant (i.e., invariant under changes in position, scale, and orientation) is a demanding task in automated image analysis. In particular, the generalized Hough transform (GHT) is a well-known algorithm for the recognition of complex patterns out of edge binary images even with disconnected boundaries or corrupted by noise. In this work we present a space multiplexed optical implementation of the GHT which, by exploiting the redundancy derived from multiview sensing of a two-dimensional image and its out- of-focus capture with an adequate pupil array, allows us to obtain in a single shot the GHT of this image invariant to target shift, scale, and orientation. Experimental validation of the working principle is presented, along with an assessment of the robustness of the system against noise in the input.