Constant beamwidth generalised sidelobe canceller

In this paper, we proposed a constant beamwidth discrete Fourier transform (DFT) beamformer based on the generalised sidelobe canceller (GSC). Broadband signals are decomposed into frequency bins which are grouped into octaves and tapered individually. The resulting beampattern possesses constant beamwidth across the entire operating spectrum, thus ensuring uniform spatial resolution. Further incorporation of the GSC allows adaptive nulling of interference to coincide with uniform resolution, enhancing the beamformer’s performance. However, modification to the constraint equation of the standard GSC is required to account for the frequency-dependent weighting of sensors

Combined conjugate and pupil adaptive optics in widefield microscopy

Traditionally, adaptive optics (AO) systems for microscopy have focused on AO at the pupil plane, however this produces poor performance in samples with both spatially-variant aberrations, such as non-flat sample interfaces, and spatially-invariant aberrations, such as spherical aberration due to a difference between the sample index of refraction and the sample for which the objective was designed. Here, we demonstrate well-corrected, wide field-of-view (FOV) microscopy by simultaneously correcting the two types of aberrations using two AO loops. Such an approach is necessary in wide-field applications where both types of aberration may be present, as each AO loop can only fully correct one type of aberration. Wide FOV corrections are demonstrated in a trans-illumination microscope equipped with two deformable mirrors (DMs), using a partitioned aperture wavefront (PAW) sensor to directly control the DM conjugated to the sample interface and a sensor-less genetic algorithm to control the DM conjugated to the objective’s pupil

Axial range of conjugate adaptive optics in two-photon microscopy

We describe an adaptive optics technique for two-photon microscopy in which the deformable mirror used for aberration compensation is positioned in a plane conjugate to the plane of the aberration. We demonstrate in a proof-of-principle experiment that this technique yields a large field of view advantage in comparison to standard pupil-conjugate adaptive optics. Further, we show that the extended field of view in conjugate AO is maintained over a relatively large axial translation of the deformable mirror with respect to the conjugate plane. We conclude with a discussion of limitations and prospects for the conjugate AO technique in two-photon biological microscopy

Resolution considerations in spatially variant sensors

Log polar transformations for space variant systems have been proposed and used in active vision research. The idea is to generate an image with a varying resolution over a wide angle field of view. The fovea is of high resolution and the periphery is of exponentially reduced resolution. The justifications for such a sensor are: (i) it provides high resolution and a wide viewing angle, (ii) feature invariance in the fovea simplifies foveation, and (iii) it allows multiresolution analysis. The receptor density of the human retina is very high, i.e. of the order of 106 receptors at the fovea. The question is, what resolution should space variant active vision systems have? Real visual sensors have been implemented but is the resolution produced high enough? This paper investigates the resolution requirements of a space variant sensor by simulation for a tracking system using raytracing<br /

Recent Progress in Image Deblurring

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented.Comment: 53 pages, 17 figure

Computational Imaging Approach to Recovery of Target Coordinates Using Orbital Sensor Data

This dissertation addresses the components necessary for simulation of an image-based recovery of the position of a target using orbital image sensors. Each component is considered in detail, focusing on the effect that design choices and system parameters have on the accuracy of the position estimate. Changes in sensor resolution, varying amounts of blur, differences in image noise level, selection of algorithms used for each component, and lag introduced by excessive processing time all contribute to the accuracy of the result regarding recovery of target coordinates using orbital sensor data. Using physical targets and sensors in this scenario would be cost-prohibitive in the exploratory setting posed, therefore a simulated target path is generated using Bezier curves which approximate representative paths followed by the targets of interest. Orbital trajectories for the sensors are designed on an elliptical model representative of the motion of physical orbital sensors. Images from each sensor are simulated based on the position and orientation of the sensor, the position of the target, and the imaging parameters selected for the experiment (resolution, noise level, blur level, etc.). Post-processing of the simulated imagery seeks to reduce noise and blur and increase resolution. The only information available for calculating the target position by a fully implemented system are the sensor position and orientation vectors and the images from each sensor. From these data we develop a reliable method of recovering the target position and analyze the impact on near-realtime processing. We also discuss the influence of adjustments to system components on overall capabilities and address the potential system size, weight, and power requirements from realistic implementation approaches

Assimilating SAR-derived water level data into a hydraulic model: a case study

Satellite-based active microwave sensors not only provide synoptic overviews of flooded areas, but also offer an effective way to estimate spatially distributed river water levels. If rapidly produced and processed, these data can be used for updating hydraulic models in near real-time. The usefulness of such approaches with real event data sets provided by currently existing sensors has yet to be demonstrated. In this case study, a Particle Filter-based assimilation scheme is used to integrate ERS-2 SAR and ENVISAT ASAR-derived water level data into a one-dimensional (1-D) hydraulic model of the Alzette River. Two variants of the Particle Filter assimilation scheme are proposed with a global and local particle weighting procedure. The first option finds the best water stage line across all cross sections, while the second option finds the best solution at individual cross sections. The variant that is to be preferred depends on the level of confidence that is attributed to the observations or to the model. The results show that the Particle Filter-based assimilation of remote sensing-derived water elevation data provides a significant reduction in the uncertainty at the analysis step. Moreover, it is shown that the periodical updating of hydraulic models through the proposed assimilation scheme leads to an improvement of model predictions over several time steps. However, the performance of the assimilation depends on the skill of the hydraulic model and the quality of the observation data