The origin of the super-resolution via a nonlinear thin film

In laser applications, resolutions beyond the diffraction limit can be obtained with a thin film of strong optical nonlinear effect. The optical index of the silicon thin film is modified with the incident laser beam as a function of the local field intensity n(r) similar to E-2(r). For ultrathin films of thickness d << lambda the transmitted light through the film forms a profile of annular rings. Therefore, the device can be related to the realization of super-resolution with annular pupils. Theoretical analysis shows that the focused light spot appears significantly reduced in comparison with the diffraction limit that is determined by the laser wavelength and the numerical aperture of the converging lens. Analysis on the additional optical transfer function due to the thin film confirms that the resolving power is improved in the high spatial frequency region. (C) 2007 Published by Elsevier B.V.

Low-Power Super-resolution Readout with Antimony Bismuth Alloy Film as Mask layer

Sb-Bi alloy films are proposed as a new kind of super-resolution mask layer with low readout threshold power. Using the Sb-Bi alloy film as a mask layer and SiN as a protective layer in a read-only memory disc, the super-resolution pits with diameters of 380 nm are read out by a dynamic setup, the laser wavelength is 780 nm and the numerical aperture of pickup lens is 0.45. The effects of the Sb-Bi thin film thickness, laser readout power and disc rotating velocity on the readout signal are investigated. The results show that the threshold laser power of super-resolution readout of the Sb-Bi mask layer is about 0.5 mW, and the corresponding carrier-to-noise ratio is about 20 dB at the film thickness of 50 nm. The super-resolution mechanism of the Sb-Bi alloy mask layer is discussed based on its temperature dependence of reflection.

A microfluidic device for high density hydrodynamic cell trapping, growth and super-resolution imaging

Super-Resolution imaging techniques such as Fluorescent Photo-Activation Localisation Microscopy (FPALM) have created a powerful new toolkit for investigating living cells, however a simple platform for growing, trapping, holding and controlling the cells is needed before the approach can become truly widespread. We present a microfluidic device formed in polydimethylsiloxane (PDMS) with a fluidic design which traps cells in a high-density array of wells and holds them very still throughout the life cycle, using hydrodynamic forces only. The device meets or exceeds all the necessary criteria for FPALM imaging of Schizosaccharomyces pombe and is designed to remain flexible, robust and easy to use. © 2011 IEEE.

A multi-frame image super-resolution method

Multi-frame image super-resolution (SR) aims to utilize information from a set of low-resolution (LR) images to compose a high-resolution (HR) one. As it is desirable or essential in many real applications, recent years have witnessed the growing interest in the problem of multi-frame SR reconstruction. This set of algorithms commonly utilizes a linear observation model to construct the relationship between the recorded LR images to the unknown reconstructed HR image estimates. Recently, regularization-based schemes have been demonstrated to be effective because SR reconstruction is actually an ill-posed problem. Working within this promising framework, this paper first proposes two new regularization items, termed as locally adaptive bilateral total variation and consistency of gradients, to keep edges and flat regions, which are implicitly described in LR images, sharp and smooth, respectively. Thereafter, the combination of the proposed regularization items is superior to existing regularization items because it considers both edges and flat regions while existing ones consider only edges. Thorough experimental results show the effectiveness of the new algorithm for SR reconstruction. (C) 2009 Elsevier B.V. All rights reserved.

Gaussian diffraction model for Sb thin films in super-resolution near-field structure

SPIE

Partially Supervised Neighbor Embedding for Example-Based Image Super-Resolution

Neighbor embedding algorithm has been widely used in example-based super-resolution reconstruction from a single frame, which makes the assumption that neighbor patches embedded are contained in a single manifold. However, it is not always true for complicated texture structure. In this paper, we believe that textures may be contained in multiple manifolds, corresponding to classes. Under this assumption, we present a novel example-based image super-resolution reconstruction algorithm with clustering and supervised neighbor embedding (CSNE). First, a class predictor for low-resolution (LR) patches is learnt by an unsupervised Gaussian mixture model. Then by utilizing class label information of each patch, a supervised neighbor embedding is used to estimate high-resolution (HR) patches corresponding to LR patches. The experimental results show that the proposed method can achieve a better recovery of LR comparing with other simple schemes using neighbor embedding.

Super-resolution in confocal scanning microscopy: generalized inversion formulae

It was shown in previous papers that the resolution of a confocal scanning microscope can be significantly improved by measuring, for each scanning position, the full diffraction image and by inverting these data to recover the value of the object at the confocal point. In the present work, the authors generalize the data inversion procedure by allowing, for reconstructing the object at a given point, to make use of the data samples recorded at other scanning positions. This leads them to a family of generalized inversion formulae, either exact or approximate. Some previously known formulae are re-derived here as special cases in a particularly simple way.

Super-resolution in confocal scanning microscopy: II :The incoherent case

For pt.I see ibid. vol.3, p.195 (1987). The authors have shown that the resolution of a confocal scanning microscope can be improved by recording the full image at each scanning point and then inverting the data. These analyses were restricted to the case of coherent illumination. They investigate, along similar lines, the incoherent case, which applies to fluorescence microscopy. They investigate the one-dimensional and two-dimensional square-pupil problems and they prove, by means of numerical computations of the singular value spectrum and of the impulse response function, that for a signal-to-noise ratio of, say 10%, it is possible to obtain an improvement of approximately 60% in resolution with respect to the conventional incoherent light confocal microscope. This represents a working bandwidth of 3.5 times the Rayleigh limit.

Super-Resolution without Evanescent Waves

The past decade has seen numerous efforts to achieve imaging resolution beyond that of the Abbe-Rayleigh diffraction limit. The main direction of research alining to break this limit seeks to exploit the evanescent components containing fine detail of the electromagnetic field distribution at the Immediate proximity of the object. Here, we propose a solution that removes the need for evanescent fields. The object being imaged or stimulated with subwavelangth accuracy does not need to be In the immediate proximity of the superlens or field concentrator: an optical mask can be designed that creates constructive Interference of waves known as superoscillation, leading to a subwavelength focus of prescribed size and shape in a field of view beyond the evanescent fields, when illuminated by a monochromatic wave. Moreover, we demonstrate that such a mask may be used not only as a focusing device but also as a super-resolution imaging device.

Optical super-resolution through super-oscillations

We demonstrate that a quasi-periodic array of nanoholes in a metal screen can focus light into subwavelength spots in the far-field without contributions from evanescent fields. The subwavelength spots were observed with a conventional optical microscope and mapped to the far-field. We relate the formation of subwavelength light localizations in the far-field to the phenomenon of super-oscillations. This effect offers a new way to achieve subwavelength imaging, which differs from approaches based on the recovery of evanescent fields.

A Single-Frame Super-Resolution Innovative Approach

Super-resolution refers to the process of obtaining a high resolution image from one or more low resolution images. In this work, we present a novel method for the super-resolution problem for the limited case, where only one image of low resolution is given as an input. The proposed method is based on statistical learning for inferring the high frequencies regions which helps to distinguish a high resolution image from a low resolution one. These inferences are obtained from the correlation between regions of low and high resolution that come exclusively from the image to be super-resolved, in term of small neighborhoods. The Markov random fields are used as a model to capture the local statistics of high and low resolution data when they are analyzed at different scales and resolutions. Experimental results show the viability of the method.

An Improved Color Video Super-Resolution Using Kernel Regression and Fuzzy Enhancement

An improved color video super-resolution technique using kernel regression and fuzzy enhancement is presented in this paper. A high resolution frame is computed from a set of low resolution video frames by kernel regression using an adaptive Gaussian kernel. A fuzzy smoothing filter is proposed to enhance the regression output. The proposed technique is a low cost software solution to resolution enhancement of color video in multimedia applications. The performance of the proposed technique is evaluated using several color videos and it is found to be better than other techniques in producing high quality high resolution color videos