We present a number of autofocusing methods in lighting microscopy for its use in diatom identifica tion. Among these, the Tenengrad method has been considered one of the best. The basic requirements for a practical autofocusing system are speed, sharpness and robustness to noise. Recently other focus measures based on a modified Laplacian method are said to per form better than Tenengrad. We investigate two sound methods based on a modified Tenengrad and a modi fied Laplacian. Measurements show that they provide a reliable and suitable focus measure that outperform similar methods. We investigate the window size anal ysis dependency and perform an univariate analysis on the focus measures. The focusing techniques are im plemented in an automatic slide scanning system for diatom detection and identification for its use in the ADIAC project. 1

AOLI (Adaptive Optics Lucky Imager) is a state-of-art instrument that combines adaptive optics (AO) and lucky imaging (LI) with the objective of obtaining diffraction limited images in visible wavelength at mid-and big-size ground-based telescopes.The key innovation of AOLI is the development and use of the new TP3-WFS (Two Pupil Plane Positions Wavefront Sensor). The TP3-WFS, working in visible band, represents an advance over classical wavefront sensors such as the Shack-Hartmann WFS (SH-WFS) because it can theoretically use fainter natural reference stars, which would ultimately provide better sky coverages to AO instruments using this newer sensor. This paper describes the software, algorithms and procedures that enabled AOLI to become the first astronomical instrument performing real-time adaptive optics corrections in a telescope with this new type of WFS, including the first control-related results at the William Herschel Telescope (WHT).

Abstract. We present a geometric sensor to restore the local tip-tilt in a segmented surface using the Van Dam and Lane algorithm [M. A. van Dam and R. G. Lane, Appl. Opt. 41(26), 5497-5502 (2002)]. The paper also presents an implementation of this algorithm using graphical processing units as specialized hardware. This compute unified device architecture implementation achieves real-time results inside the stability time of the atmosphere for resolutions of up to 1024 × 1024 pixels. © The Authors.Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

No abstract

Abstract-In this paper, a new methodology for extracting motion patterns is applied to optical flow estimation in the presence of multiple motions. The proposed approximation deals with the problem in two stages. In the first one, the most important motions are segmented; in the second one, the optical flow is estimated on the basis of the motions detected in the previous stage. To extract relevant motions, a new approach based on a spatio-temporal filtering is presented. The approach groups together parts of a moving object that have been separated into various filter responses because of the object's spatial structure, thereby avoiding the spatial dependency problem associated with a representation based on spatio-temporal filters. The proposed model, therefore, generates one "motion pattern" for each motion detected in the sequence. To obtain an optical flow estimation, which is able to represent multiple velocities, the gradient constraint is applied to the output of each filter so that multiple estimations of the velocity at the same location may be obtained. For each "motion pattern" detected in the previous stage, the velocities at a given point corresponding to the same motion are then combined using a probabilistic approach. In the application to optical flow estimation, the use of "motion patterns" allows multiple velocities to be represented, while the combination of estimations from different filters helps reduce the aperture problem. This technique is illustrated on real and simulated data sets, including sequences with occlusion and transparencies.

The combination of Lucky Imaging with a low order adaptive optics system was demonstrated very successfully on the Palomar 5m telescope nearly 10 years ago. It is still the only system to give such high-resolution images in the visible or near infrared on ground-based telescope of faint astronomical targets. The development of AOLI for deployment initially on the WHT 4.2 m telescope in La Palma, Canary Islands, will be described in this paper. In particular, we will look at the design and status of our low order curvature wavefront sensor which has been somewhat simplified to make it more efficient, ensuring coverage over much of the sky with natural guide stars as reference object. AOLI uses optically butted electron multiplying CCDs to give an imaging array of 2000 x 2000 pixels.

The New Robotic Telescope (NRT) is an international collaboration to build and operate a 4m diameter fully robotic telescope. The telescope will take advantage of the superb atmospheric conditions at the Observatory of the Roque de los Muchachos (ORM). In conjunction with a large aperture, entirely robotic operation, quick response, and a set of versatile instrumentation in the optical and near-infrared this guarantees a high scientific impact focused mainly in the area of time domain astronomy. This paper presents the scientific motivation and the status of the project, discussing possible technical solutions under evaluation for the optics, mechanics and control system.

No abstract