An Efficient Correction Algorithm for Eliminating Image Misalignment Effects on Co-Phasing Measurement Accuracy for Segmented Active Optics Systems.

The phase diversity (PD) algorithm is an image-based co-phasing error detection method for segmented mirror synthetic aperture optical systems. Particle swarm optimization (PSO) is suitable for PD for its fast convergence speed and simple structure. However, with the increase of the numbers of subapertures, optimization of cost function formed by the PD algorithm becomes a high-dimension non-linear optimization problem, which would lead PSO to result in a premature solution. Regarding the problem above, this paper presented a modified PSO in the PD algorithm to co-phase the segmented primary mirror, which overcame drawbacks of the traditional PSO, such as premature convergence and deactivation of particles, and enhanced the dig ability of the algorithm. Vast simulation results show that the modified PSO in the PD algorithm can effectively restore the segmented primary mirror, reducing the peak-to-valley (PV) value to 0.0012λ and the root mean square error to 0.0007λ, and raising the Strehl ratio to over 0.999. A comparison was also conducted to show that the modified PSO has advantages over two existing algorithms in higher accuracy and faster convergence speed.

Phase diversity experimental results: deconvolution of ν Scorpii

Time‐of‐flight (TOF) and resolution modeling (RM) algorithms are frequently used in clinical PET images, and inclusion of these corrections should measurably improve image quality. We quantified the effects of these correction algorithms on reconstructed images via the following metrics: recovery coefficients (RCs), contrast‐to‐noise ratio (CNR), noise‐power spectrum (NPS), modulation transfer function (MTF), and the full width at half maximum (FWHM) of a point source. The goal of this experiment was to assess the effects of the correction algorithms when applied singly or together. Two different phantom tests were performed and analyzed by custom software. FWHM and MTF were measured using capillary tube point sources, while RCs, CNR, and NPS were measured using an image quality body phantom. Images were reconstructed with both TOF and RM, only TOF, only RM, or neither correction. The remaining reconstruction parameters used the standard clinical protocol. RM improved RCs, FWHM, and MTF, without increasing overall noise significantly. TOF improves CNR for small objects FWHM or MTF but did not decrease noise. RCs were not statistically improved by enabling these algorithms. Inclusion of both correction algorithms in image reconstruction provides an overall improvement to all metrics relative to the uncorrected image, but not by a significant margin in multiple aspects.

There is high demand for deploying real-time or near real-time implementation of image reconstruction techniques for intelligence, surveillance, and reconnaissance (ISR) systems, as well as biomedical systems, and border applications. While many image restoration techniques have been implemented, their computational complexity makes them unsuitable for real-time systems. This work presents massively parallelized algorithms for two and three-dimensional image reconstruction of objects using deconvolution and bispectrum techniques. Speckle imaging (SI) techniques are more preferred for phase reconstruction because of its high restoration quality at the lower values of signal-to-noise ratio (SNR), especially for smaller targets, and its shift-invariant property which makes it insensitive to random motion of an object. This work proposes, a novel strategy for parallelization of recursive bispectrum algorithm. Furthermore, parallel bispectrum speckle imaging technique is used as an initial step for parallelized multi-frame blind deconvolution (MFBD) image restoration algorithm in order to speed-up the reconstruction process for anisoplanatic, long horizontal path imaging. The parallel hybrid Bispectrum- MFBD (B-MFBD) technique, through massive parallelization, provides significantly large improvement to both bispectrum SI and MFBD parts of the hybrid algorithm. The work also investigates phase diversity (PD) technique as the special case of MFBD algorithm, where the object is observed with a stack of intentionally defocused images. The known defocused information between phases is used to estimate the object and aberration function. The multi-plane PD was implemented for wide field fluorescence microscopy imaging of three-dimensional objects. The PD algorithm was subsequently used to generate 3D point cloud data for the image from its single view.

The well known phase diversity technique has long been used as a premier passive imaging method to mitigate the degrading effects of atmospheric turbulence on incoherent optical imagery. Typically, an iterative, slow method is applied that uses the Zernike basis set and 2-D Fourier transforms in the reconstruction process. In this paper, we demonstrate a direct method for estimating the un-aberrated object brightness from phase or phase difference estimates that 1) does not require the use of the Zernike basis set or the intermediate determination of the generalized pupil function, 2) directly determines the optical transfer function without the requirement for an iterative sequence of 2-D Fourier Transforms, 3) provides a more accurate result than the Zernike-based approaches since there are no Zernike series truncation errors, 4) lends itself to fast and parallel implementation, and 5) can use stochastic search methods to rapidly determine simultaneous phases or phase differences required to determine the correct optical transfer function estimate. As such, this new implementation of phase diversity provides potentially faster, more accurate results than previous approaches yet still retains inherent compatibility with the traditional Zernike-based methods. The theoretical underpinnings of this new method along with demonstrative computer simulation results are presented.

We compare the performance of four metrics for use in a phase diversity algorithm. Three of the metrics utilize a regularization based on the signal-to-noise ratio.

A theoretical description of Phase Diversity is done in some detail to lay the foundations for the experimental effort. The Phase Diversity algorithm is formulated in the context of nonlinear programming where a metric is developed and then minimized. This development will show how the Zernike coefficients can be solved for directly using nonlinear optimization techniques. Computer simulations are used to validate the algorithms and techniques. The results of the computer simulations are shown. Once the confidence of the algorithms and techniques are established in the computer simulations, they are used on actual laboratory data. Detailed discussion of the laboratory implementation will be described and the laboratory results will be shown.

A compact charge coupled device (CCD) camera system has been designed and characterized for use in the six inch manipulator (SIM) at the Nova laser facility. The camera system has been designed to directly replace the 35 mm film packages currently used in SIM-based x-ray imaging diagnostics. The unit’s electronic package has been constructed for small size and high thermal conductivity which reduces the overall camera size and improves its performance when operated within the vacuum environment of the Nova target chamber. Measurements of the x-ray imager’s contrast transfer function (CTF) were made under a variety of operating conditions on a static x-ray Manson source using both the CCD and Kodak T-Max 3200 film as recording media. The CTF data were converted to an equivalent modulation transfer function (MTF). The MTF plots show that the microchannel plate has a uniform response within our measurement accuracy along its strips. In a direction normal to the strip, however, the MTF is reduced due to the slant angle of the pores in the MCP. The measurements show that the CCD camera has a lower MTF response than T-MAX film for all spatial frequencies and configurations measured. However, data obtained from the film exhibited reciprocity failure and border effects that are not observed in the CCD data. Measurements indicate that the signal-to-noise ratio for the CCD data is four to six times larger than that obtained with film and higher photon flux levels were recorded. The CCD-based diagnostic offers immediate access to the data, improved dynamic range, and reduced turnaround time, while eliminating the need for film development, digitization, equipment, and personnel.

The wavefront passed through the atmosphere will produce different degree of distortion, due to atmospheric disturbances, defocus, aberration and etc. Distortion of wavefront can result in image degradation. Conventional methods typically use adaptive optics to correct the degradation. Correction system is complex and requires three parts, including wavefront detection, wavefront reconstruction, wavefront correction, and each part requires very precise control. In order to simplify the system structure, we use Hartmann - Shack wavefront sensor to get wavefront information, and then reconstruct the degenerated image using software restoration method. The paper introduces the background and significance of Hartmann-Shack wavefront sensor, summarizes the wavefront reconstruction principle. Then we analyze the general model of optical transfer function (OTF) and the way to calculate the OTF of diffraction limited incoherent image system. Take the actual situation into consideration, wavefront distortion is unavoidable, so we deduce the method to calculate OTF with wavefront distortion. Based on different wavefront detection error and the image restoration quality, we concluded the allowed maximum detection error under different peak value of wavefront.

The graphoepitaxy DSA process relies on lithographically created confinement wells to perform directed self-assembly in the thin film of the block copolymer. These self-assembled patterns are then etch transferred into the substrate. The conventional DUV immersion or EUV lithography is still required to print these confinement wells, and the lithographic patterning residual errors propagate to the final patterns created by DSA process. DSA proximity correction (PC), in addition to OPC, is essential to obtain accurate confinement well shapes that resolve the final DSA patterns precisely. In this study, we proposed a novel correction flow that integrates our co-optimization algorithms, rigorous 2-D DSA simulation engine, and OPC tool. This flow enables us to optimize our process and integration as well as provides a guidance to design optimization. We also showed that novel RET techniques such as DSA-Aware assist feature generation can be used to improve the process window. The feasibility of our DSA correction framework on large layout with promising correction accuracy has been demonstrated. A robust and efficient correction algorithm is also determined by rigorous verification studies. We also explored how the knowledge of DSA natural pitches and lithography printing constraints provide a good guidance to establish DSA-Friendly designs. Finally application of our DSA full-chip computational correction framework to several real designs of contact-like holes is discussed. We also summarize the challenges associated with computational DSA technology.

Wavefront sensorless adaptive optics system for extended objects based on linear phase diversity technique

In engineering practice, anuloid surfaces are produced that are subject to strict requirements in terms of accuracy (e.g., in the bearing industry). Roundness is also often measured. The accuracy of the roundness measurement does not only depend on the accuracy of a particular metrological system. The setting of the component on the measuring device can also have a significant influence on the accuracy of the measurement. The axis of the measured surface must be perpendicular to the section in which the roundness is measured. Tilting the measured surface causes a systematic measurement error, which depends on the size of the tilt angle and the parameters of the measured surface. This study presents mathematical relations for the calculation of this error when measuring roundness on an anuloid surface. Mathematical relations for the internal and external surfaces formed by the inner and outer parts of the anuloid are derived herein. There is also a theoretical analysis of the influence of inclination and the parameters of the measured surface on the size of this error. Theoretically calculated values were compared with practically measured values of roundness. The error had a negative effect on the accuracy of the roundness measurement. It affected the roundness value, the second harmonic component, and also the roundness profile itself.

Within the new air traffic management concept, using the Global Navigation Satellite System (GNSS), it is assumed that distance measurement equipment (DME) will be retained. The results of research carried out by several authors have confirmed that global navigation satellite systems (GNSS) can be put out of operation in cases of interference. Therefore, it is very timely to investigate the accuracy and resistance to interference of DME systems. The presented work contains the results of research in the field of assessment of the accuracy and resistance of a DME system, which works in conditions of narrowband interference, using modeling and simulation. Based on the derived model of the DME measurement signal, its parameters, and narrowband interference, algorithms for processing the measurement signals of a DME system in conditions of narrowband interference were derived. A quasi-optimal nonlinear filtering method was used in the derivation of the measurement signal-processing algorithms. A quadratic loss function was used as an optimality criterion, which allows us to obtain the results of measuring the parameters of the DME measurement signal as a minimum of the a posteriori mean error. Within this method, Gaussian approximation and large and small parameter methods were used. Simulation of the operation of the DME system confirmed that the measurement accuracy of this system depends on the stability of the frequency of the DME support generator, and also depends on the signal-to-noise ratio and the signal-to-interference ratio of the DME receiver input. Comparing the results of the DME system receiver designed by us with the parameters listed in in published works that discuss the accuracy of this system, we can conclude that its accuracy is much better. The simulation results confirmed that the potential accuracy of the distance measurement is equal to 2.2 m. However, the mentioned algorithms require substantial simplification to be used for real-time signal processing. This will be our next research direction.

Star tracker has been widely used as a precise and reliable device for the attitude measuring of a spacecraft. The accuracy of star location will affect the accuracy of star identification and finally the accuracy of attitude measurement. This paper proposed a novel method to locate the star position with the phase transfer function (PTF). The numerical expressions are deduced with the diffraction model of the star point in 1-D and given directly in 2-D. Then calculation is performed and the accuracy is better than 2.1% pixels (SNR=20) with a 3×3 window of airy disk, which is higher than the traditional centroid method. Different sizes of the airy disk from 3 to 6 are simulated with PTF method and we find that the optimal window size is 3 to 5. Finally the Additive Gaussian Noise with SNR from 2 to 40 is introduced to evaluate the novel method and compare it with the traditional centroid method. The accuracy of the new method can reach better than 2.5% pixels and it is much robust than the traditional centroid method, which proves that the method we proposed has a good performance under the noise environment.

A fully automatic redeye detection and correction algorithm is presented to address the redeye artifacts in digital photos. The algorithm contains a redeye detection part and a correction part. The detection part is modeled as a feature based object detection problem. Adaboost is used to simultaneously select features and train the classifier. A new feature set is designed to address the orientation-dependency problem associated with the Haar-like features commonly used for object detection design. For each detected redeye, a correction algorithm is applied to do adaptive desaturation and darkening over the redeye region.