Digital micromirror device (DMD) serves in a major part of computational optical setups as a means of encoding an image by a desired pattern. The most prominent is its usage in the so-called single-pixel camera experiments, where light reflected from a DMD is collected onto a single-pixel detector. This often requires efficient and homogenous collection of light from a relatively large chip on a small area of an optical fiber or spectrometer slit. This effort is moreover complicated by the fact that the DMD acts as a diffractive element – this becomes especially prominent in the infrared (IR) spectral region. The light diffraction causes serious spectral inhomogeneities in the light collection. We studied the effect of light diffraction via whiskbroom hyperspectral camera. Based on the knowledge, we designed a variety of different approaches to light collection, which use a combination lenses, off-axis parabolic mirrors, diffuser, light concentrator, and integrating spheres. By using an identical optical setup we mapped the efficiency and spectral homogeneity of each of the approaches. The selected benchmark was the ability to collect the light into fiber spectrometers working in the visible and IR range (up to 2500 nm). As expected, we have found the integrating spheres to provide homogeneous light collection, which however suffers from a low efficiency. The best compromise between the performance parameters was provided by a combination of an engineered diffuser with an off-axis parabolic mirror. We used this configuration to create a computational microscope able to carry out hyperspectral imaging of a sample in a broad spectral range (400-2500 nm) and to map photoluminescence (PL) decay via time-correlated single photon counting technique. This allowed us to create one-to-one maps of absorption and PL inhomogeneities in samples. We see such setup as an ideal tool to study properties of luminophores and the effect of inhomogeneities on the PL properties.
Pb(Zr,Ti)O3 (PZT) is a ferroelectric material interesting for its high dielectric constant and piezoelectric response. PZT thin films can be prepared by various methods, e.g. pulsed laser deposition, chemical vapor deposition, sol-gel and, most frequently, sputtering. Though the magnetron sputtering is used more frequently, PZT thin films can be prepared also by ion-beam sputtering (IBS). In this paper we study the deposition process of PZT thin films in our IBS system with a possibility of ion-beam assisted deposition (IBAD), which has the advantage that more energy can be added to the growing layer. We show how in our system the resulting layers, mainly their quality, the Pb content, which is important for the creation of the perovskite crystal structure, and the resulting crystal structure are influenced by the oxygen flux during the deposition for the samples grown on the silicon substrate with and without an intermediate Ti seeding layer.
Compressed sensing (CS) is a branch of computational optics able to reconstruct an image (or any other information) from a reduced number of measurements – thus significantly saving measurement time. It relies on encoding the detected information by a random pattern and consequent mathematical reconstruction. CS can be the enabling step to carry out imaging in many time-consuming measurements. The critical step in CS experiments is the method to invoke encoding by a random mask. Complex devices and relay optics are commonly used for the purpose. We present a new approach of creating the random mask by using laser speckles from coherent laser light passing through a diffusor. This concept is especially powerful in laser spectroscopy, where it does not require any complicated modification of the current techniques. The main advantage consist in the unmatched simplicity of the random pattern generation and a versatility of the pattern resolution. Unlike in the case of commonly used random masks, here the pattern fineness can be adjusted by changing the laser spot size being diffused. We demonstrate the pattern tuning together with the connected changes in the pattern statistics. In particular, the issue of patterns orthogonality, which is important for the CS applications, is discussed. Finally, we demonstrate on a set of 200 acquired speckle patterns that the concept can be successfully employed for single-pixel camera imaging. We discuss requirements on detector noise for the image reconstruction.
Spectrum of light which is emitted or reflected by an object carries immense amount of information about the object. A simple piece of evidence is the importance of color sensing for human vision. Combining an image acquisition with efficient measurement of light spectra for each detected pixel is therefore one of the important issues in imaging, referred as hyperspectral imaging. We demonstrate a construction of a compact and robust hyperspectral camera for the visible and near-IR spectral region. The camera was designed vastly based on off-shelf optics, yet an extensive optimization and addition of three customized parts enabled construction of the camera featuring a low f-number (F/3.9) and fully concentric optics. We employ a novel approach of compressed sensing (namely coded aperture snapshot spectral imaging, abbrev. CASSI). The compressed sensing enables to computationally extract an encoded hyperspectral information from a single camera exposition. Owing to the technique the camera lacks any moving or scanning part, while it can record the full image and spectral information in a single snapshot. Moreover, unlike the commonly used compressed sensing table-top apparatuses, the camera represents a portable device able to work outside a lab. We demonstrate the spectro-temporal reconstruction of recorded scenes based on 90×90 random matrix encoding. Finally, we discuss potential of the compressed sensing in hyperspectral camera.