Pietro Ferraro

Bio: Pietro Ferraro is an academic researcher from National Research Council. The author has contributed to research in topics: Digital holography & Holography. The author has an hindex of 61, co-authored 653 publications receiving 12666 citations. Previous affiliations of Pietro Ferraro include Aeritalia & Centre national de la recherche scientifique.

Tilted objects EFI in digital holography by two different numerical approaches

Abstract: Limited depth of field (DOF) is one of the main shortage for many optical imaging systems. This is a limitation that precludes to get in focus, in a single plane, objects that are located at different distances, but that fall in the same field of view. Furthermore, the depth of field is reduced as much as greater is the requirement for a high magnification and to obtain an extended focus image (EFI) of these objects remains one of the major challenges. In this work we propose and compare two different approaches to build the EFI of holograms recorded on a tilted plane. In the first case, a simplified three-dimensional (3D) formulation of the angular spectrum method (ASM) is proposed. It allows to generate the entire stack of propagated images in a single shot. In the second approach, a numerical cubic phase plate (CPP) is included into the reconstruction process of digital holograms with the aim to enhancing DOF of optical imaging system. Theoretical formulations of the two approaches are supported by experimental evidences. The obtained results show that the proposed strategies allow to reconstruct effectively an EFI from holograms recorded on an inclined plane.

An investigation on deep learning approaches for diatoms classification

Abstract: Diatoms are one of the largest groups of microalgae present in marine, freshwater and transitional environments and their reactivity to environmental changes makes them suitable to be employed as biomarkers for monitoring tasks. Anyway, their presence in a large number of species makes it arduous to perform diatoms taxonomy during monitoring tasks considering that, to date, analysis is conducted by marine biologists on the basis of their own experience and, hence, in a subjective way. Hence, the need for automatic and objective methodologies for the identification and classification of diatoms samples rises. Research efforts in the field of Computer Vision led to a plethora of highly effective deep learning strategies surpassing human capabilities for image classification, as showed in the recent Imagenet challenge editions where they were initially introduced. Despite the very promising results of the proposed solutions, the difficulty arises to determine which technique is most suitable among them for real tasks and in particular for diatoms classification. This work proposes an end-to-end pipeline for automatic recognition of diatoms, acquired by means of holographic microscopy in water samples, employing deep learning techniques. In particular the most recently introduced Convolution Neural Networks (CNNs) architectures have been deeply investigated and compared in order to highlight the pros and cons of each of them. Moreover, in order to feed the CNNs training stages with a suitable amount of labeled data, a strategy to build a synthetic dataset, starting from a single image per class available from commercial glass slides specifically prepared for taxonomy purposes, is introduced. Besides, models ensembling strategies, in order to improve the single model scores, have been exploited. Finally, the proposed approach has been validated employing a dataset built up of holographic images of diatoms sampled in natural water bodies.

A method for total noise removal in digital holography based on enhanced grouping and sparsity enhancement filtering

Abstract: In digital holography (DH), the coherent nature of the employed light sources severely degrades the holographic reconstructions due to a mixture of speckle and incoherent additive noise. These can affect both the visual quality in holographic imaging and display, and the accuracy of quantitative phase-contrast reconstructions. Typically, the noise problem is tackled by reducing the illumination coherence, thus the most intuitive way involves the recording of multiple uncorrelated holograms to be incoherently combined. This framework is known as Multi-Look DH (MLDH). However, single shot recordings are highly desirable in DH, and numerical methods are required to go beyond the improvement bound of ML techniques. Among the existing image processing methods, the 3D Block Matching filtering (BM3D) has shown the best performance. Here we present the MLDH-BM3D, a method specifically suitable to filter DH images that combines the two aforementioned strategies to overcome their respective limitations. We demonstrate the effectiveness of this framework in three different experimental situations, i.e. reconstructions of single wavelength holograms and color holograms in the visible region and the challenging case of the Infrared Radiation Digital Holography (IRDH) reconstructions, where a very severe noise degradation occurs.

Quantitative phase contrast microscopy in turbid microfluidic channels by digital holography

Abstract: Clear coherent imaging through turbid media is a challenging task showing potentialities in the newest applications in microfluidics. If the targets of interest are dipped into turbid fluids, the medium particles act as strong scatterers, resulting in speckle noise and hindering a clear vision by conventional Optics. Conversely, Digital Holography is able to overcome this limit in case of both flowing and quasi-static media. If the liquid flows at sufficient speed into the microfluidic channel, the Doppler effect can be exploited to record the only useful information. In the quasistatic case, a method is proposed to reduce the speckle noise by processing multiple holograms. Experiments have been carried out to show that a clear amplitude and phase-contrast mapping is achievable by speckle reduction while preserving the image resolution.

Reflective grating interferometer: a versatile and simple system for education in optics

Abstract: Recently has been developed a two component interferometer that has several advantages when used for eduction and training in optics. It is a wavefront division interferometer based on the use of a reflective grating that is used for recombination of two portion of one plane wavefront, obtained using a low cost parabolic mirror of commercial telescopes. The alignment operation is performed setting the mirror and the reflective grating at 90 degree each other. Interference fringe pattern are presented in all the volume in front the reflective grating interferometer and a screen or a CCD camera without lens can be used to visualize fringes. The interferometer being made of only two components is also very stable. Fringe pattern spacing and orientation can be simply changed rotating the mirror on a vertical axis or tilting it respectively. The fact that mirror and the grating are adjacent has some advantages on the pedagogical side because students can understand better how relative movements of the two components affect the changes in the fringe pattern. This interferometer is used not only to study interferometry but can be used also to study geometrical optics using the fringe pattern as a grid to perform Ronchi test. In such a way it is possible to conduct investigation on aberrations of optical components (Spherical, astigmatism and coma) or determine focal lengths lenses by using Moire effect. In conclusion the RGI is a system that comprises, at same time, in its operation different areas of the optics: interferometry, diffraction, wavefront picture of light, geometrical optics, testing. Examples of application for education purposes are described.

Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry

Abstract: A fast-Fourier-transform method of topography and interferometry is proposed. By computer processing of a noncontour type of fringe pattern, automatic discrimination is achieved between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour-generation techniques. The method has advantages over moire topography and conventional fringe-contour interferometry in both accuracy and sensitivity. Unlike fringe-scanning techniques, the method is easy to apply because it uses no moving components.

Fiber grating sensors

Abstract: We review the recent developments in the area of optical fiber grating sensors, including quasi-distributed strain sensing using Bragg gratings, systems based on chirped gratings, intragrating sensing concepts, long period-based grating sensors, fiber grating laser-based systems, and interferometric sensor systems based on grating reflectors.