We present a fast point cloud clustering technique which is suitable for outlier detection, object segmentation and region labeling for large multi-dimensional data sets. The basis is a minimal data structure similar to a kd-tree which enables us to detect connected subsets very fast. The proposed algorithms utilizing this tree structure are parallelizable which further increases the computation speed for very large data sets. The procedures given are a vital part of the data preprocessing. They improve the input data properties for a more reliable computation of surface measures, polygonal meshes and other visualization techniques. In order to show the effectiveness of our techniques we evaluate sets of point clouds from different 3D scanning devices.

Spatial light modulators enable arbitrary control of the intensity of optical light fields and facilitate a variety of applications in biology, astronomy, and atomic, molecular, and optical physics. For coherent light fields, holography, implemented through arbitrary phase modulation, represents a highly power-efficient technique to shape the intensity of light patterns. Here, we introduce and benchmark a spatial light modulator based on a piston micromirror array. In particular, we utilize the reflection-based device to demonstrate arbitrary beam shaping in the ultraviolet (UV) regime at a wavelength of 322 nm. We correct aberrations of the reflected wave front and show that the modulator does not add detectable excess phase noise to the reflected light field. We utilize the intrinsically low latency of the architecture to demonstrate fast switching of arbitrary light patterns synchronized with short laser pulses at an update rate of 1 kHz. Finally, we outline how the modulator can act as an important component of a zone-based architecture for a neutral-atom quantum computer or simulator, including UV wavelengths.

The digitalization of real-world objects is of great importance in various application domains. E.g. in industrial processes quality assurance is very important. Geometric properties of workpieces have to be measured. Traditionally, this is done with gauges which is somewhat subjective and time-consuming. We developed a robust optical laser scanner for the digitalization of arbitrary objects, primary, industrial workpieces. As measuring principle we use triangulation with structured lighting and a multi-axis locomotor system. Measurements on the generated data leads to incorrect results if the contained error is too high. Therefore, processes for geometric inspection under non-laboratory conditions are needed that are robust in permanent use and provide high accuracy as well as high operation speed. The many existing methods for polygonal mesh optimization produce very esthetic 3D models but often require user interaction and are limited in processing speed and/or accuracy. Furthermore, operations on optimized meshes consider the entire model and pay only little attention to individual measurements. However, many measurements contribute to parts or single scans with possibly strong differences between neighboring scans being lost during mesh construction. Also, most algorithms consider unsorted point clouds although the scanned data is structured through device properties and measuring principles. We use this underlying structure to achieve high processing speeds and extract intrinsic system parameters and use them for fast pre-processing.

The present article discusses an optical concept for the characterization of diffractive micromirror arrays (MMAs) within an extended wavelength range from the deep ultra-violet up to near-infrared. The task derives from the development of a novel class of MMAs that will support programmable diffractive properties between 240 nm and 800 nm. The article illustrates aspects of the achromatic system design that comprises the reflective beam homogenization with divergence control and coherence management for an appropriate MMA illumination as well as the transfer of phase modulating MMA patterns into intensity profiles for contrast imaging. Contrast measurements and grey scale imaging demonstrate the operation of the characterization system and reflect the encouraging start of technology development for multispectral, diffractive MMAs.

Micromirror arrays (MMA) are spatial light modulators (SLM) used in a wide variety of applications for structured light manipulation i.e. structured illumination microscopy. In our setup, we use a combination of two micromirror arrays, which allow not only to spatially structure the light in the field of view, but also to control the direction and angle of the incident light. In order to achieve this, a first MMA is imaged in the focal plane and used as a black and white (or even greyscale) mask. With a fully illuminated objective, this image would normally be formed from the complete light cone. By imaging the second MMA onto the backfocal plane of the objective only a portion of the light cone is used to form the image. This enables avoiding the unwanted illumination of out of focus objects. The MMAs in our setup consist of an array of 256x256 micromirrors, that can each be individually and continuously tilted up to 450nm, allowing the creation of greyscale images in real time in the illumination pattern. The mirrors themselves can be tilted for times as short as 10 mu s up to several seconds. This gives unprecedented control over the illumination times and intensities in the sample. Furthermore, our enhanced coating technology yields a high reflectivity over a broad optical spectrum (240- 1000nm). Overall, the setup allows targetted illumination of subcellular regions enabling the precise, localized activation of optogenetic probes or the activation and deactivation of signaling cascades using photo-activated ion-channels

Increased spatial resolution and revisit time of payloads operating in the infrared spectral region can offer unprecedented advantages to Earth Observation. This, however, poses several technological challenges, such as large array detector availability and data bandwidth. In this paper, we present a super-resolved demonstrator—based on a compressive sensing architecture—which is being developed to address enhanced performance in terms of at-ground spatial resolution, on-board data processing and encryption functionalities for Earth Observation payloads. The demonstrator’s architecture is here presented, together with its working principle, main features and the approach used for image reconstruction.