Efficient entangled photon pair sources are the main component for several applications based on quantum imaging. Specifically for ghost imaging, different wavelengths of signal (imaging photons) and idler (interaction with the object) photons are desired. An efficient and narrowband generation of entangled photons exploiting spontaneous parametric down-conversion using periodically poled (pp) nonlinear crystals is therefore a fundamental preliminary requirement to achieve (the process of) ghost imaging. This work presents the design and implementation of a precise and efficient crystalheater as a variable photon pair source and compares the achieved experimental values of the SPDC-wavelengths with theoretical calculations. A periodically poled nonlinear crystal from potassium titanyl phosphate (ppKTP) can generate various non-degenerate wavelengths from a pump radiation of 405 nm by temperature changes and satisfaction of energy conservation and quasi-phase-matching conditions. For this purpose, the crystal is securely housed in a custom-built mechanical mount. A computation and adjustment of various control parameters, as well as a precise determination of the current temperature via two temperature sensors allow the heater to set the target temperature with an accuracy of 0.1 °C±0.015 °C. A method for the theoretical determination of the temperature-dependent shift of the nondegenerate wavelengths, provides a foundation from which experimental verification of achievable wavelengths and intensities can be compared. By experimental verification, the efficiency and functionality of the photon pair source and SPDC-process is verified. These presented investigations and the design of the crystal-heater provide the basis for a precise and effective photon pair source, for subsequent studies in the field of ghost imaging.
Surface inspection in industrial automated processes is very often challenging. Especially the detection of transparent liquid materials such as water represent a major challenge for standard imaging systems. One approach to overcome the limitation of these imaging systems lies in the exploitation of the polarization effect. This effect surely can only be applied if the contaminants have polarizing features but can help to use invisible characteristics of light for quality inspection tasks. In this work investigations on surfaces which are contaminated with water will be presented. Therefore, an imaging system using an RGB dome light illumination was set up in combination with a four-channel polarizing camera. The dome light, which is equipped with three different LED wavelengths, will be mixed so that the illumination which hits the sample is completely unpolarized. So, any effect on the surface which leads to a polarizing effect can be observed. The system delivers a four-channel image with different polarization angles that have to be processed. Therefore, an algorithm realizes a demosaicing which separates the four different polarized pixels into individual images. Based on this, the stokes equation which allows the calculation of the degree of polarization and the angle of polarization has to be processed for the image presentation. To achieve a better visualization of the degree of polarization an HSV-transformation based on the polarization parameters was also realized.
KEYWORDS: Image processing, Image acquisition, Algorithm development, Field programmable gate arrays, Cameras, System on a chip, Principal component analysis
Through the acquisition and processing of several spectral channels within the multispectral data, the demands on signal processing and data handling increase enormously. With the help of intelligent signal pre-processing on programmable system on chip platforms (pSoC), captured data can be corrected and evaluated directly after image acquisition. PSoC combine the advantages of freely programmable logic (FPGA) and sequential processor systems (ARM technology) and significantly increase the integration density of embedded image processing systems. However, the design effort for these systems is increasing strongly, so that hardware/software co-design approaches must be used for implementation. The paper covers the design methodology, the implementation and the evaluation of multichannel acquisition systems using multispectral image sensors as an example.
Passive-stereo-imaging as a part of three-dimensional image processing can be applied for many use cases where a depth information is necessary. This is often the case when classical two dimensional image processing get to its borders. Passive-stereo needs at minimum two images of the same object of interest. An initial one-time system calibration is absolutely essential. The usage of more than two sensors offer more system stability and reduce hidden image elements. A variant of semi-global-matching algorithm is used to find the matching points in the image pair and is implemented in the FPGA. The lateral shift of two matching points is called disparity. All disparity values together result in a disparity image which is the basis for a point cloud. By using embedded technologies, a compact and portable acquisition system could be realized. Programmable system-on-chip (PSoC) combining FPGA and ARM computing power in one chip design. This technology is an ideal solution to so acquire the images from the image sensor and calculate the disparity images.
This paper presents the latest developments on filter-wheel based multispectral imaging systems as well as their extension to making 3D images. The system, capable of producing high spatial resolution images on a spectrum spanning from 400nm to 1050nm (in 12 steps of 50nm (configurable) with 50nm or less bandwidth) can be used, without hardware change. To produce 3D image stacks where the height resolution is given by the numerical aperture of the optics used and the reproducibility of the image plane moving motor is also possible. This paper introduces the reader to spectral imaging and to 3D measurement techniques. The main parameters and relevant publications of/about the industrial monocular multispectral 3D-Imager are then presented. Correction of chromatic aberration on filter wheel system, a key idea for 3D image reconstruction, is revised. 3D imaging capabilities of the system as well as proper calibration are introduced. Selected applications and algorithms are presented towards to the end of the paper.
KEYWORDS: Principal component analysis, Optical filters, Image processing, Image filtering, Field programmable gate arrays, Cameras, Picosecond phenomena, Imaging systems, Image acquisition, System on a chip
The acceleration of the acquisition of spectral images and their processing is important for the acceptance of these measurement methods in quality assurance and inspection. A frequently used preprocessing step is the Principal Component Analysis (PCA). It is used in variations, for example, for segmentation, spectral decomposition or data compression. The presented implementation calculates the PCA for the 12 spectral image channels of a filter wheel camera parallel to image acquisition. This includes the determination of the covariance matrix, the calculation of the main components and the transformation of the data. The parallel processing during the sequential imaging acquisition is performed on a System-on-a-programmable-chip (SoPC) Xilinx Zynq-7000 directly within the camera. The algorithm is partitioned into hard and software components and implemented in the field programmable gate array (FPGA) fabric as well as the ARM processor core firmware of the SoPC. In order to ensure the steps of the image acquisition chain in addition to the calculation, the system was implemented as an asymmetric multiprocessing system (AMP) with individual processors. For additional acceleration under static conditions (e.g. continuous testing in the manufacturing process), the feature vector can be stored as a calibration value. The calculation is reduced to the transformation of the data.
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