Does median filtering truly preserve edges better than linear filtering?

Image processing researchers commonly assert that "median filtering is better than linear filtering for removing noise in the presence of edges." Using a straightforward large-$n$ decision-theory framework, this folk-theorem is seen to be false in general. We show that median filtering and linear filtering have similar asymptotic worst-case mean-squared error (MSE) when the signal-to-noise ratio (SNR) is of order 1, which corresponds to the case of constant per-pixel noise level in a digital signal. To see dramatic benefits of median smoothing in an asymptotic setting, the per-pixel noise level should tend to zero (i.e., SNR should grow very large). We show that a two-stage median filtering using two very different window widths can dramatically outperform traditional linear and median filtering in settings where the underlying object has edges. In this two-stage procedure, the first pass, at a fine scale, aims at increasing the SNR. The second pass, at a coarser scale, correctly exploits the nonlinearity of the median. Image processing methods based on nonlinear partial differential equations (PDEs) are often said to improve on linear filtering in the presence of edges. Such methods seem difficult to analyze rigorously in a decision-theoretic framework. A popular example is mean curvature motion (MCM), which is formally a kind of iterated median filtering. Our results on iterated median filtering suggest that some PDE-based methods are candidates to rigorously outperform linear filtering in an asymptotic framework.Comment: Published in at http://dx.doi.org/10.1214/08-AOS604 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Optimization of the ionization time of an atom with tailored laser pulses: a theoretical study

How fast can a laser pulse ionize an atom? We address this question by considering pulses that carry a fixed time-integrated energy per-area, and finding those that achieve the double requirement of maximizing the ionization that they induce, while having the shortest duration. We formulate this double-objective quantum optimal control problem by making use of the Pareto approach to multi-objetive optimization, and the differential evolution genetic algorithm. The goal is to find out how much a precise time-profiling of ultra-fast, large-bandwidth pulses may speed up the ionization process with respect to simple-shape pulses. We work on a simple one-dimensional model of hydrogen-like atoms (the P\"oschl-Teller potential), that allows to tune the number of bound states that play a role in the ionization dynamics. We show how the detailed shape of the pulse accelerates the ionization process, and how the presence or absence of bound states influences the velocity of the process

Adaptive multiscale detection of filamentary structures in a background of uniform random points

We are given a set of $n$ points that might be uniformly distributed in the unit square $[0,1]^2$. We wish to test whether the set, although mostly consisting of uniformly scattered points, also contains a small fraction of points sampled from some (a priori unknown) curve with $C^{\alpha}$-norm bounded by $\beta$. An asymptotic detection threshold exists in this problem; for a constant $T_-(\alpha,\beta)>0$, if the number of points sampled from the curve is smaller than $T_-(\alpha,\beta)n^{1/(1+\alpha)}$, reliable detection is not possible for large $n$. We describe a multiscale significant-runs algorithm that can reliably detect concentration of data near a smooth curve, without knowing the smoothness information $\alpha$ or $\beta$ in advance, provided that the number of points on the curve exceeds $T_*(\alpha,\beta)n^{1/(1+\alpha)}$. This algorithm therefore has an optimal detection threshold, up to a factor $T_*/T_-$. At the heart of our approach is an analysis of the data by counting membership in multiscale multianisotropic strips. The strips will have area $2/n$ and exhibit a variety of lengths, orientations and anisotropies. The strips are partitioned into anisotropy classes; each class is organized as a directed graph whose vertices all are strips of the same anisotropy and whose edges link such strips to their ``good continuations.'' The point-cloud data are reduced to counts that measure membership in strips. Each anisotropy graph is reduced to a subgraph that consist of strips with significant counts. The algorithm rejects $\mathbf{H}_0$ whenever some such subgraph contains a path that connects many consecutive significant counts.Comment: Published at http://dx.doi.org/10.1214/009053605000000787 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

GEMS: Goals, Expectations, Measurements and Strategies for Critical Thinking and Decision-Making

GEMS are sparkling stones that are very attractive and precious. Its attractiveness and spackles are derived from the meticulous precision of the way the stones were cut. It takes a perfect design, planning and execution to achieve such results. GEMS is also an acronym that represents leadership excellence. GEMS stands for Goals, Expectations, Measurements, and Strategies. The team concluded that a leadership handbook for the 21st century must be simple but forward looking in addressing the issues of today and the immediate future. The handbook is broken down into sections that are easy to follow. It is design for leaders to think critically in all aspects of the business. Effective leaders must know and understand clearly the goals or mission of the company. The handbook provides a detailed but simple way on how to formulate company’s goals. Shared goals are more effective than top down goals as it gives all employees or participants of the company ownership which translates to empowerment and accountability. Expectations are standards developed by each company and are designed to maintain its competitive advantage. Critical thinking is an expectation that organizations look for from the employees. This handbook laid out the techniques leaders need to know to achieve such goals. As goals and expectations are clearly defined and preached to the leader’s constituency another important element of GEMS is Measurement. Once goals are set and agreed with by all stakeholders the next important step is the development of a measuring tool. The company’s success is dependent upon the effective execution of each processes or tasks of each and every employees in the organization. The handbook covered the key role that Human Resources played in ensuring its success. Finally, the last element of GEMS is strategy. It outlined in detail how a global leader can be consistently successful in this dynamic business environment. The important topics discussed were goal setting, resources required, timeline, and actual execution of the strategy. A successful implementation of a leadership handbook will only be achieved if the organizational leadership accepts and understands the necessity of thinking outside the box. This handbook is intentionally design to force global leaders to think beyond the norm of doing business. It forces all employees and senior leadership to be self-critical and accept changes as the new normal in doing business. We all hope that you enjoy the fruits of this excellent leadership handbook

Enrichment of bacterial strains for the biodegradation of endocrine disrupting compounds from sediments of the Pearl River delta (PRD)

info:eu-repo/semantics/publishedVersio

Library of high and mid-resolution spectra in the CaII H & K, Hα, Hβ, NaI D_1, D_2, and HeI D3 line regions of F, G, K and M field stars

In this work we present spectroscopic observations centered in the spectral lines most widely used as optical indicators of chromospheric activity (Hα, Hβ, CaII H & K, and HeI D_3) in a sample of F, G, K and M chromospherically inactive stars. The spectra have been obtained with the aim of providing a library of high and mid-resolution spectra to be used in the application of the spectral subtraction technique to obtain the active-chromosphere contribution to these lines in chromospherically active single and binary stars. This library can also be used for spectral classification purposes. A digital version with all the spectra is available via ftp and the World Wide Web (WWW) in both ASCII and FITS formats

Constructed wetlands as nature-based solutions for wastewater treatment in the hospitality industry: a review

The hospitality industry is increasing its awareness of how the integration of nature-based solutions can decrease its environmental impact while maintaining or increasing the service level of the sector. Constructed wetlands (CWs) constitute a promising sustainable solution for proper in situ domestic wastewater treatment. This literature review elucidates the status of CWs implementation in the hospitality industry to help foster the exchange of experiences in the field and deliver examples of approaches in different contexts to support future applications of this technology. Most of the studies reported in the literature were conducted in Europe, but studies emanating from Asia and South America are also available. The design of CWs, the horizontal and vertical subsurface flow CWs (HSFCW, VSFCW), and hybrid systems have been reported. The average removal efficiencies of the systems ranged from 83 to 95% for biochemical oxygen demand, 74 to 94% for chemical oxygen demand, 78 to 96% for total suspended solids, 75 to 85% for ammonium, 44 to 85% for ammonia, 50 to 73% for nitrate, 57 to 88% for total Kjeldahl nitrogen, 51 to 58% total nitrogen, and 66 to 99% for total phosphorus. The majority of the systems were implemented as decentralized treatment solutions using HSFCWs, with the second most common design being the hybrid CW systems in order to reduce area requirements, increase treatment efficiency, and prevent clogging. Overall, CWs are a promising sustainable solution which may support access to adequate sanitation worldwide as well as safe wastewater recycling and reuse, leading to more sustainable tourist destinations.info:eu-repo/semantics/publishedVersio

Enhancing the Structure of the WRF-Hydro Hydrologic Model for Semiarid Environments

In August 2016, the National Weather Service Office of Water Prediction (NWS/OWP) of the National Oceanic and Atmospheric Administration (NOAA) implemented the operational National Water Model (NWM) to simulate and forecast streamflow, soil moisture, and other model states throughout the contiguous United States. Based on the architecture of the WRF-Hydro hydrologic model, the NWM does not currently resolve channel infiltration, an important component of the water balance of the semiarid western United States. Here, we demonstrate the benefit of implementing a conceptual channel infiltration function (from the KINEROS2 semidistributed hydrologic model) into the WRF-Hydro model architecture, configured as NWM v1.1. After calibration, the updated WRF-Hydro model exhibits reduced streamflow errors for the Walnut Gulch Experimental Watershed (WGEW) and the Babocomari River in southeast Arizona. Model calibration was performed using NLDAS-2 atmospheric forcing, available from the NOAA National Centers for Environmental Prediction (NCEP), paired with precipitation forcing from NLDAS-2, NCEP Stage IV, or local gauge precipitation. Including channel infiltration within WRF-Hydro results in a physically realistic hydrologic response in the WGEW, when the model is forced with high-resolution, gauge-based precipitation in lieu of a national product. The value of accounting for channel loss is also demonstrated in the Babocomari basin, where the drainage area is greater and the cumulative effect of channel infiltration is more important. Accounting for channel infiltration loss thus improves the streamflow behavior simulated by the calibrated model and reduces evapotranspiration bias when gauge precipitation is used as forcing. However, calibration also results in increased high soil moisture bias, which is likely due to underlying limitations of the NWM structure and calibration methodology.University Corporation for Atmospheric Science (UCAR) COMET Cooperative Project; NOAA Joint Technology Transfer Initiative (JTTI) Federal Grant [NA17OAR4590183]6 month embargo; published online 22 April 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]