Anna Pastuszczak

Sub-wavelength diffraction-free imaging with low-loss metal-dielectric multilayers

We demonstrate numerically the diffraction-free propagation of sub-wavelength sized optical beams through simple elements built of metal-dielectric multilayers. The proposed metamaterial consists of silver and a high refractive index dielectric, and is designed using the effective medium theory as strongly anisotropic and impedance matched to air. Further it is characterised with the transfer matrix method, and investigated with FDTD. The diffraction-free behaviour is verified by the analysis of FWHM of PSF in the function of the number of periods. Small reflections, small attenuation, and reduced Fabry–Pérot resonances make it a flexible diffraction-free material for arbitrarily shaped optical planar elements with sizes of the order of one wavelength.

Optimized low-loss multilayers for imaging with sub-wavelength resolution in the visible wavelength range

We optimize the effective skin-depth and resolution of Ag-TiO2, Ag-SrTiO3, and Ag-GaP multilayers for imaging with sub-wavelength resolution. In terms of transmission and resolution, the optimized multilayers outperform simple designs based on combined use of effective medium theory, impedance matching and Fabry–Perot resonances. For instance, an optimized Ag-GaP multilayer consisting of only 17 layers, operating at the wavelength of 490 nm and having a total thickness equal to one wavelength, combines 78% intensity transmission with a resolution of 60 nm. It is also shown that use of the effective medium theory leads to sub-optimal multilayer designs with respect to the trade-off between the skin depth and resolution already when the period of the structure is on the order of 40 nm or larger.

Sensitivity of imaging properties of metal-dielectric layered flat lens to fabrication inaccuracies

We characterize the sensitivity of imaging properties of a layered silver-TiO2 flat lens to fabrication inaccuracies. The lens is designed for approximately diffraction-free imaging with subwavelength resolution at distances in the order of a wavelength. Its operation may be attributed to self-collimation with a secondary role of Fabry-Perot resonant transmission, even though the first order effective medium description of the structure is inaccurate. Super-resolution is maintained for a broad range of overall thicknesses and the total thickness of the multilayer is limited by absorption. The tolerance analysis indicates that the resolution and transmission efficiency are highly sensitive to small changes of layer thicknesses.

Efficient adaptation of complex-valued noiselet sensing matrices for compressed single-pixel imaging.

Minimal mutual coherence of discrete noiselets and Haar wavelets makes this pair of bases an essential choice for the measurement and compression matrices in compressed-sensing-based single-pixel detectors. In this paper, we propose an efficient way of using complex-valued and nonbinary noiselet functions for object sampling in single-pixel cameras with binary spatial light modulators and incoherent illumination. The proposed method allows us to determine m complex noiselet coefficients from m+1 binary sampling measurements. Further, we introduce a modification to the complex fast noiselet transform, which enables computationally efficient real-time generation of the binary noiselet-based patterns using efficient integer calculations on bundled patterns. The proposed method is verified experimentally with a single-pixel camera system using a binary spatial light modulator.

Compressive phase-only filtering at extreme compression rates

Abstract We introduce an efficient method for the reconstruction of the correlation between a compressively measured image and a phase-only filter. The proposed method is based on two properties of phase-only filtering: such filtering is a unitary circulant transform, and the correlation plane it produces is usually sparse. Thanks to these properties, phase-only filters are perfectly compatible with the framework of compressive sensing. Moreover, the lasso-based recovery algorithm is very fast when phase-only filtering is used as the compression matrix. The proposed method can be seen as a generalization of the correlation-based pattern recognition technique, which is hereby applied directly to non-adaptively acquired compressed data. At the time of measurement, any prior knowledge of the target object for which the data will be scanned is not required. We show that images measured at extremely high compression rates may still contain sufficient information for target classification and localization, even if the compression rate is high enough, that visual recognition of the target in the reconstructed image is no longer possible. The method has been applied by us to highly undersampled measurements obtained from a single-pixel camera, with sampling based on randomly chosen Walsh–Hadamard patterns.

Engineering the point spread function of layered metamaterials

Layered metal-dielectric metamaterials have filtering properties both in the frequency domain and in the spatial frequency domain. Engineering their spatial filtering response is a way of designing structures with specific diffraction properties for such applications as sub-diffraction imaging, supercollimation, or optical signal processing at the nanoscale. In this paper we review the recent progress in this field.We also present a numerical optimization framework for layered metamaterials, based on the use of evolutionary algorithms. A measure of similarity obtained using Hölder’s inequality is adapted to construct the overall criterion function. We analyse the influence of surface roughness on the quality of imaging.

Linear sub-diffraction spatial filtering with plasmonic materials

We optimise the transfer function of layered metal-dielectric metamaterials for imaging with sub-wavelength resolution, for high-pass spatial filtering, and for diffraction compensation. A variant of a genetic algorithm is used to optimise the metamaterial. The optimisation criteria include transmission, and reflection coefficients averaged over a range of spatial frequencies, and a measure of similarity between the optimised and desired transfer function. This measure is normalised using the Hölders inequality and is invariant to scaling by a multiplicative complex factor. The overall criterion is a linear combination of these three basic criteria.

Spatial filtering with rough metal-dielectric layered metamaterials

The paper presents the way that colour can serve solving the problem of calibration points indexing in a camera geometrical calibration process. We propose a technique in which indexes of calibration points in a black-and-white chessboard are represented as sets of colour regions in the neighbourhood of calibration points. We provide some general rules for designing a colour calibration chessboard and provide a method of calibration image analysis. We show that this approach leads to obtaining better results than in the case of widely used methods employing information about already indexed points to compute indexes. We also report constraints concerning the technique. Nowadays we are witnessing an increasing need for camera geometrical calibration systems. They are vital for such applications as 3D modelling, 3D reconstruction, assembly control systems, etc. Wherever possible, calibration objects placed in the scene are used in a camera geometrical calibration process. This approach significantly increases accuracy of calibration results and makes the calibration data extraction process easier and universal. There are many geometrical camera calibration techniques for a known calibration scene [1]. A great number of them use as an input calibration points which are localised and indexed in the scene. In this paper we propose the technique of calibration points indexing which uses a colour chessboard. The presented technique was developed by solving problems we encountered during experiments with our earlier methods of camera calibration scene analysis [2]-[3]. In particular, the proposed technique increases the number of indexed points points in case of local lack of calibration points detection. At the beginning of the paper we present a way of designing a chessboard pattern. Then we describe a calibration point indexing method, and finally we show experimental results. A black-and-white chessboard is widely used in order to obtain sub-pixel accuracy of calibration points localisation [1]. Calibration points are defined as corners of chessboard squares. Assuming the availability of rough localisation of these points, the points can be indexed. Noting that differences in distances between neighbouring points in calibration scene images differ slightly, one of the local searching methods can be employed (e.g. [2]). Methods of this type search for a calibration point to be indexed, using a window of a certain size. The position of the window is determined by a vector representing the distance between two previously indexed points in the same row or column. However, experiments show that this approach has its disadvantages, as described below. * E-mail: A.Nowakowski@ire.pw.edu.pl Firstly, there is a danger of omitting some points during indexing in case of local lack of calibration points detection in a neighbourhood (e.g. caused by the presence of non-homogeneous light in the calibration scene). A particularly unfavourable situation is when the local lack of detection effects in the appearance of separated regions of detected calibration points. It is worth saying that such situations are likely to happen for calibration points situated near image borders. Such points are very important for the analysis of optical nonlinearities, and a lack of them can significantly influence the accuracy of distortion modelling. Secondly, such methods may give wrong results in the case of optical distortion with strong nonlinearities when getting information about the neighbouring index is not an easy task. Beside this, the methods are very sensitive to a single false localisation of a calibration point. Such a single false localisation can even result in false indexing of a big set of calibration points. To avoid the above-mentioned problems, we propose using a black-and-white chessboard which contains the coded index of a calibration point in the form of colour squares situated in the nearest neighbourhood of each point. The index of a certain calibration point is determined by colours of four nearest neighbouring squares (Fig.1). An order of squares in such foursome is important. Because the size of a colour square is determined only by the possibility of correct colour detection, the size of a colour square can be smaller than the size of a black or white square. The larger size of a black or white square is determined by the requirements of the exact localisation step which follows the indexing of calibration points [3]. In this step, edge information is extracted from a blackand-white chessboard. This edge information needs larger Artur Nowakowski, Wladyslaw Skarbek Institute of Radioelectronics, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warszawa, A.Nowakowski@ire.pw.edu.pl Received February 10, 2009; accepted March 27, 2009; published March 31, 2009 http://www.photonics.pl/PLP

Optimisation of transmission properties and subwavelength imaging of silver-dielectric layered structures operating in the canalization regime

We analyse the subwavelength imaging properties of a flat lens consisting of alternating thin metal and dielectric layers operating in the canalization regime. We show that the skin depth of the homogenised structure may exceed by almost two orders of magnitude the skin depth of silver. Its optimisation leads to the choice of the optimal wavelength of 437 nm. In effect, the multilayer exhibits high transmission combined with subwavelength resolution at distances of several wavelengths. We show how the Fabry-Perot resonant conditions for the thickness of the structure become relaxed for thicker multilayers. Our simulations are based on the transfer and scattering matrix methods, valid for calculating either evanescent or propagating modes.

Single-pixel imaging with Morlet wavelet correlated random patterns

Single-pixel imaging is an indirect imaging technique which utilizes simplified optical hardware and advanced computational methods. It offers novel solutions for hyper-spectral imaging, polarimetric imaging, three-dimensional imaging, holographic imaging, optical encryption and imaging through scattering media. The main limitations for its use come from relatively high measurement and reconstruction times. In this paper we propose to reduce the required signal acquisition time by using a novel sampling scheme based on a random selection of Morlet wavelets convolved with white noise. While such functions exhibit random properties, they are locally determined by Morlet wavelet parameters. The proposed method is equivalent to random sampling of the properly selected part of the feature space, which maps the measured images accurately both in the spatial and spatial frequency domains. We compare both numerically and experimentally the image quality obtained with our sampling protocol against widely-used sampling with Walsh-Hadamard or noiselet functions. The results show considerable improvement over the former methods, enabling single-pixel imaging at low compression rates on the order of a few percent.