Atmospheric optical turbulence mitigation using iterative image registration and least squares lucky look fusion.

This paper presents an atmospheric optical turbulence mitigation method that uses a sequence of short-exposure frames. An iterative block matching registration method is proposed for image dewarping. The dewarped frames are combined in a least squares lucky look (LL) fusion process.

Simulation of anisoplanatic lucky look imaging and statistics through optical turbulence using numerical wave propagation: erratum.

We present an erratum to our previously published work [Appl. Opt.60, G19 (2021)APOPAI0003-693510.

Simulation of anisoplanatic lucky look imaging and statistics through optical turbulence using numerical wave propagation.

This paper investigates anisoplanatic numerical wave simulation in the context of lucky look imaging. We demonstrate that numerical wave propagation can produce root mean square (RMS) wavefront distributions and probability of lucky look (PLL) statistics that are consistent with Kolmogorov theory. However, the simulated RMS statistics are sensitive to the sampling parameters used in the propagation window.

Single-pulse, Kerr-effect Mueller matrix LiDAR polarimeter.

We present a novel light detection and ranging (LiDAR) polarimeter that enables measurement of 12 of 16 sample Mueller matrix elements in a single, 10 ns pulse. The new polarization state generator (PSG) leverages Kerr phase modulation in a birefringent optical fiber, creating a probe pulse characterized by temporally varying polarization. Theoretical expressions for the Polarization State Generator (PSG) Stokes vector are derived for birefringent walk-off and no walk-off and incorporated into a time-dependent polarimeter signal model employing multiple polarization state analyzers (PSA).

Injuries in elite women's ski jumping: surveillance through the 2017-18 FIS World Cup season.

Objectives: To describe the incidence, type, aetiology and severity of injuries sustained by the International Ski Federation World Cup level female ski jumpers during the 2017-18 season.

Design: Prospective cohort study.

Methods: Sixty-seven female ski jump athletes from 16 countries were followed throughout the 17-week winter season.

Editorial Commentary: What Is the Best Graft Source for Posterior Cruciate Ligament Reconstruction?

In 2018, the best available evidence has failed to show any significant clinical or functional difference between autograft and allograft for posterior cruciate ligament reconstruction. Autograft patients may have higher complication rates. Both groups show good functional outcome after reconstruction.

Epidemiological Trends of Anterior Cruciate Ligament Reconstruction in a Canadian Province.

Objective: To determine epidemiological trends of anterior cruciate ligament reconstruction (ACL-R) in a Canadian province, estimate the national incidence, and compare with internationally published data.

Design: Retrospective review.

Setting: All hospitals that performed ACL reconstructions in Manitoba between 1980 and 2015.

Human skin detection in the visible and near infrared.

Skin detection is a well-studied area in color imagery and is useful in a number of scenarios to include search and rescue and computer vision. Most approaches focus on color imagery due to cost and availability. Many of the visible-based approaches do well at detecting skin (above 90%) but they tend to have relatively high false-alarm rates (8%-15%).

Range separation performance and optimal pulse-width prediction of a three-dimensional flash laser detection and ranging using the Cramer-Rao bound.

This paper derives the Cramer-Rao bound (CRB) on range separation estimation of two point sources interrogated by a three-dimensional flash laser detection and ranging (LADAR) system. An unbiased range separation estimator is also derived to compare against the bound. Additionally, the CRB can be expressed as a function of two LADAR design parameters (range sampling and transmitted pulse width), which can be selected in order to optimize the expected range resolution between two point sources.

Cardinal interpolation.

A Bayesian probability density for an interpolating function is developed, and its desirable properties and practical potential are demonstrated. This density has an often needed but previously unachieved property, here called cardinal interpolation, which ensures extrapolation to the density of the least squares linear model. In particular, the mean of the cardinal interpolation density is a smooth function that intersects given (x, y) points and which extrapolates to their least squares line, and the variance of this density is a smooth function that is zero at the point x values, that increases with distance from the nearest point x value, and that extrapolates to the well-known quadratic variance function for the least squares line.