Statistical scene generation for polarimetric imaging systems

Little publicly available data exists for polarimetric measurements. When designing task specific polarimetric systems, the statistical properties of the task specific data becomes important. Until better polarimetric datasets are available to deduce statistics from, the statistics must be simulated to test instrument performance. Most imaged scenes have been shown to follow a power law power spectral density distribution, for both natural and city scenes. Furthermore, imaged data appears to follow a power law power spectral distribution temporally. We are interested in generating image sets which change over time, and at the same time are correlated between different components (spectral or polarimetric). In this brief communication, we present a framework and provide code to generate such data.Comment: 5 pages, 3 figures, 3 matlab function

Canonical Correlation Feature Selection for Sensors with Overlapping Bands: Theory and Application

The main focus of this paper is a rigorous development and validation of a novel canonical correlation feature- selection (CCFS) algorithm that is particularly well suited for spectral sensors with overlapping and noisy bands. The proposed approach combines a generalized canonical correlation analysis framework and a minimum mean-square-error criterion for the selection of feature subspaces. The latter induces ranking of the best linear combinations of the noisy overlapping bands and, in doing so, guarantees a minimal generalized distance between the centers of classes and their respective reconstructions in the space spanned by sensor bands. To demonstrate the efficacy and the scope of the proposed approach, two different applications are considered. The first one is separability and classification analysis of rock species using laboratory spectral data and a quantum-dot infrared photodetector (QDIP) sensor. The second application deals with supervised classification and spectral unmixing, and abundance estimation of hyperspectral imagery obtained from the Airborne Hyperspectral Imager sensor. Since QDIP bands exhibit significant spectral overlap, the first study validates the new algorithm in this important application context. The results demonstrate that proper postprocessing can facilitate the emergence of QDIP-based sensors as a promising technology for midwave- and longwave-infrared remote sensing and spectral imaging. In particular, the proposed CCFS algorithm makes it possible to exploit the unique advantage offered by QDIPs with a dot-in-a-well configuration, comprising their bias-dependent spectral response, which is attributable to the quantum Stark effect. The main objective of the second study is to assert that the scope of the new CCFS approach also extends to more traditional spectral sensors

Statistical Adaptive Sensing by Detectors with Spectrally Overlapping Bands

It has recently been reported that by using a spectral-tuning algorithm, the photocurrents of multiple detectors with spectrally overlapping responsivities can be optimally combined to synthesize, within certain limits, the response of a detector with an arbitrary responsivity. However, it is known that the presence of noise in the photocurrent can degrade the performance of this algorithm significantly, depending on the choice of the responsivity spectrum to be synthesized. We generalize this algorithm to accommodate noise. The results are applied to quantum-dot mid-infrared detectors with bias-dependent spectral responses. Simulation and experiment are used to show the ability of the algorithm to reduce the adverse effect of noise on its spectral-tuning capability

Generalized Algebraic Algorithm for Scene-based Nonuniformity Correction

ABSTRACT This paper presents an overview of three recently developed scene-based nonuniformity correction techniques, namely, the algebraic scene-based algorithm (ASBA), the extended radiometrically accurate scene-based algorithm (RASBA) and the generalized algebraic scene-based algorithm (GASBA). The ASBA uses pairs of image frames that exhibit one-dimension sub-pixel motion to algebraically extract estimates of bias nonuniformity. The RASBA incorporates arbitrary sub-and super-pixel two-dimensional motion in conjunction with limited perimeter-only absolute calibration to obtain radiometrically accurate estimates of the bias nonuniformity. The RASBA provides the advantage of being able to maintain radiometry in the interior photodetectors without interrupting their operation. The GASBA is a generalized non-radiometric form of the algorithm that uses image pairs with arbitrary two-dimensional motion and encompasses both the ASBA and RASBA algorithms. This generalization is accomplished by initially guaranteeing bias uniformity in the perimeter detectors. This uniformity can be achieved by first applying the ASBA estimates. The generalized algorithm is then able to automatically maintain perimeter uniformity without the need for re-application of the ASBA. Thus, the GASBA is able to operate completely in a non-radiometric mode, alleviating the need for the perimeter calibration system if desired. The generalized algorithm is applied to real infrared imagery obtained from both cooled and uncooled infrared cameras. A hardware implementation of the proposed algorithm will also be discussed along with several ongoing commercial applications of the technology

Demonstration of Bias-Controlled Algorithmic Tuning of Quantum Dots in a Well (DWELL) MidIR Detectors

The quantum-confined Stark effect in intersublevel transitions present in quantum-dots-in-a-well (DWELL) detectors gives rise to a midIR spectral response that is dependent upon the detector\u27s operational bias. The spectral responses resulting from different biases exhibit spectral shifts, albeit with significant spectral overlap. A postprocessing algorithm was developed by Sakoglu that exploited this bias-dependent spectral diversity to predict the continuous and arbitrary tunability of the DWELL detector within certain limits. This paper focuses on the experimental demonstration of the DWELL-based spectral tuning algorithm. It is shown experimentally that it is possible to reconstruct the spectral content of a target electronically without using any dispersive optical elements for tuning, thereby demonstrating a DWELL-based algorithmic spectrometer. The effects of dark current, detector temperature, and bias selection on the tuning capability are also investigated experimentally

An overview of polarimetric sensing techniques and technology with applications to different research fields

We report the main conclusions from an interactive, multidisciplinary workshop on “Polarimetric Techniques and Technology”, held on March 24-28 2014 at the Lorentz Center in Leiden, the Netherlands. The work- shop brought together polarimetrists from different research fields. Participants had backgrounds ranging from academia to industrial RD. Here we provide an overview of polarimetric instrumentation in the optical regime geared towards a wide range of applications: atmospheric remote sensing, target detection, astronomy, biomedical applications, etc. We identify common approaches and challenges. We list novel polarimetric techniques and polarization technologies that enable promising new solutions. We conclude with recommendations to the polarimetric community at large on joint efforts for exchanging expertise

Economic Impact of Dengue Illness and the Cost-Effectiveness of Future Vaccination Programs in Singapore

Dengue illness is a tropical disease transmitted by mosquitoes that threatens more than one third of the worldwide population. Dengue has important economic consequences because of the burden to hospitals, work absenteeism and risk of death of symptomatic cases. Governments attempt to reduce the disease burden using costly mosquito control strategies such as habitat reduction and spraying insecticide. Despite such efforts, the number of cases remains high. Dengue vaccines are expected to be available in the near future and there is an urgent need to evaluate their cost-effectiveness, i.e. whether their cost will be justified by the reduction in disease burden they bring. For such an evaluation, we estimated the economic impacts of dengue in Singapore and the expected vaccine costs for different prices. In this way we estimated price thresholds for which vaccination is not cost-effective. This research provides useful estimates that will contribute to informed decisions regarding the adoption of dengue vaccination programs

Statistical Analysis of Molecular Signal Recording

A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a “molecular ticker tape”, in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.United States. Defense Advanced Research Projects Agency. Living Foundries ProgramGoogle (Firm)New York Stem Cell Foundation. Robertson Neuroscience Investigator AwardNational Institutes of Health (U.S.) (EUREKA Award 1R01NS075421)National Institutes of Health (U.S.) (Transformative R01 1R01GM104948)National Institutes of Health (U.S.) (Single Cell Grant 1 R01 EY023173)National Institutes of Health (U.S.) (Grant 1R01DA029639)National Institutes of Health (U.S.) (Grant 1R01NS067199)National Science Foundation (U.S.) (CAREER Award CBET 1053233)National Science Foundation (U.S.) (Grant EFRI0835878)National Science Foundation (U.S.) (Grant DMS1042134)Paul G. Allen Family Foundation (Distinguished Investigator in Neuroscience Award

Enhancement of the point-spread function for imaging in scattering media by use of polarization-difference imaging

J. Opt. Soc. Am. A, Volume 17, No. 1, pp. 1-10, (January 2000)Polarization-difference (PD) imaging techniques have been demonstrated to improve the detectability of target features that are embedded in scattering media. The improved detectability occurs for both passive imaging in moderately scattering media (,5 optical depths) and active imaging in more highly scattering media. These improvements are relative to what is possible with equivalent polarization-blind, polarization-sum (PS) imaging under the same conditions. In this investigation, the point-spread functions (PSFà à ¢ s) for passive PS and PD imaging in single-scattering media are studied analytically, and Monte Carlo simulations are used to study the PSFà à ¢ s in single- and moderately multiple-scattering media. The results indicate that the PD PSF can be significantly narrower than the corresponding PS PSF, implying that better images of target features with high-spatial-frequency information can be obtained by using differential polarimetry in scattering media. Although the analysis was performed for passive imaging at moderate optical depths, the results lend insight into experiments that have been performed in more highly scattering media with active imaging methods to help mitigate the effects of multiple scattering

Noise equalization in Stokes parameter images obtained by use of variable-retardance polarimeters

Optics Letters, Volume 25, No. 16, pp. 1198-1200 (August 15, 2000)An imaging variable retardance polarimeter was developed and tested by Tyo and Turner [Proc. SPIE 3753, 214 (1999)]. The signal-to-noise ratio (SNR) in the reconstructed polarization images obtained with this system varied for the four Stokes parameters. The difference in SNR is determined to be due to differences in the Euclidean lengths of the rows of the synthesis matrix used to reconstruct the Stokes parameters from the measured intensity data. I equalize (and minimize) the lengths of the rows of this matrix by minimizing the condition number of the synthesis matrix, thereby maximizing the relative importance of each of the polarimeter measurements. The performance of the optimized system is demonstrated with simulated data, and the SNR is shown to increase from a worst case of 23.1 dB for the original settings to a worst case of 15.0 dB for the optimized system