Adaptive structure tensors and their applications

The structure tensor, also known as second moment matrix or Förstner interest operator, is a very popular tool in image processing. Its purpose is the estimation of orientation and the local analysis of structure in general. It is based on the integration of data from a local neighborhood. Normally, this neighborhood is defined by a Gaussian window function and the structure tensor is computed by the weighted sum within this window. Some recently proposed methods, however, adapt the computation of the structure tensor to the image data. There are several ways how to do that. This article wants to give an overview of the different approaches, whereas the focus lies on the methods based on robust statistics and nonlinear diffusion. Furthermore, the dataadaptive structure tensors are evaluated in some applications. Here the main focus lies on optic flow estimation, but also texture analysis and corner detection are considered

Rain-induced turbulence and air-sea gas transfer

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C07009, doi:10.1029/2008JC005008.Results from a rain and gas exchange experiment (Bio2 RainX III) at the Biosphere 2 Center demonstrate that turbulence controls the enhancement of the air-sea gas transfer rate (or velocity) k during rainfall, even though profiles of the turbulent dissipation rate ɛ are strongly influenced by near-surface stratification. The gas transfer rate scales with ɛ inline equation for a range of rain rates with broad drop size distributions. The hydrodynamic measurements elucidate the mechanisms responsible for the rain-enhanced k results using SF6 tracer evasion and active controlled flux technique. High-resolution k and turbulence results highlight the causal relationship between rainfall, turbulence, stratification, and air-sea gas exchange. Profiles of ɛ beneath the air-sea interface during rainfall, measured for the first time during a gas exchange experiment, yielded discrete values as high as 10−2 W kg−1. Stratification modifies and traps the turbulence near the surface, affecting the enhancement of the transfer velocity and also diminishing the vertical mixing of mass transported to the air-water interface. Although the kinetic energy flux is an integral measure of the turbulent input to the system during rain events, ɛ is the most robust response to all the modifications and transformations to the turbulent state that follows. The Craig-Banner turbulence model, modified for rain instead of breaking wave turbulence, successfully predicts the near-surface dissipation profile at the onset of the rain event before stratification plays a dominant role. This result is important for predictive modeling of k as it allows inferring the surface value of ɛ fundamental to gas transfer.This work was funded by a generous grant from the David and Lucile Packard Foundation and the Lamont-Doherty Earth Observatory Climate Center. Additional funding was provided by the National Science Foundation (OCE-05-26677) and the Office of Naval Research Young Investigator Program (N00014-04-1-0621)

A Total Least Squares Framework for Low-Level Analysis of Dynamic Scenes and Processes

We present a new method to simultaneously estimate optical flow fields and parameters of dynamic processes, violating the standard brightness change constraint equation. This technique constitutes a straightforward generalization of the standard brightness constancy assumption. Using TLS estimation the spatiotemporal brightness structure is analyzed in an entirely symmetric way with respect to the spatial and temporal coordinates. We directly incorporate nonlinear brightness changes based upon differential equations of the underlying processes

Mixed OLS-TLS for the estimation of Dynamic Processes With a Linear Source Term

We present a novel technique to eliminate strong biases in parameter estimation were part of the data matrix is not corrupted by errors. Problems of this type occur in the simultaneous estimation of optical flow and the parameter of linear brightness change as well as in range flow estimation. For attaining highly accurate optical flow estimations under real world situations as required by a number of scientific applications, the standard brightness change constraint equation is violated. Very often the brightness change has to be modelled by a linear source term. In this problem as well as in range flow estimation, part of the data term consists of an exactly known constant. Total least squares (TLS) assumes the error in the data terms to be identically distributed, thus leading to strong biases in the equations at hand. The approach presented in this paper is based on a mixture of ordinary least squares (OLS) and total least squares, thus resolving the bias encountered in TLS alone. Apart from a thorough performance analysis of the novel estimator, a number of applications are presented

Dense parameter fields from total least squares

A method for the interpolation of parameter fields estimated by total least squares is presented. This is applied to the study of dynamic processes where the motion and further values such as divergence or brightness changes are parameterised in a partial differential equation

Evaluierung eines Protein-Dockingsystems durch Leave-One-Out-Test

Ackermann F, Herrmann G, Posch S, Sagerer G. Evaluierung eines Protein-Dockingsystems durch Leave-One-Out-Test. Informatik Aktuell. 1996:130-137.Beschrieben wird die Realisierung und Evaluierung eines wissensbasierten Ansatzes zur Lösung des Protein-Protein-Dockingproblems, der eine Anwendung des semantischen Netzwerksystems ERNEST darstellt. Aufbauend auf den Ergebnissen einer Segmentierung von dreidimensionalen Oberflächen strukturaufgelöster Proteine werden vom System unter Einbeziehung von Funktionen, die geometrische Merkmale berechnen und bewerten, mögliche Dockingpositionen für zwei betrachtete Proteine vorgeschlagen. Berechnet werden unter anderem der Steric Clash und die Volumendifferenz zu paarender Dockingregionen. Das Dockingsystem wurde für 17 bekannte Proteinkomplexe, bei denen die korrekte relative Position beider Proteine experimentell bestimmt wurde, trainiert und mit der Leave-One-Out-Methode getestet. In der überwiegenden Mehrzahl der Fälle werden vollautomatisch in kurzer Rechenzeit vom System die korrekten Dockingpositionen mit einer Genauigkeit von wenigen Angstroem DRMS vorhergesagt