Sub-optimal solutions to track detection problem using graph theoretic concepts

This paper demonstrates how the problem of tracking targets, which appear as either straight or curved lines in two-dimensional display images (or data images) can be formulated in terms of a directed weighted graph model and how dynamic programming techniques can be efficiently applied to reach an optimal or sub-optimal solution. In general, track detection algorithms providing optimal solutions have good detective ability, but most of them suffer from the inability to detect discontinuous lines or to resolve efficiently pairs of crossing lines. A sub-optimal solution is provided that efficiently overcomes these weaknesses. We focus on modeling the track detection problem in terms of a graph, formulating fast sequential/parallel sub-optimal track detection algorithms and testing them on simulated data in order to show their detective ability. Moreover, we specify the conditions under which sub-optimal algorithms can perform at least as well as their corresponding optimal algorithms. This is significant for the track detection problem where fast, accurate and real-time detection is considered a necessity.     

Trusting the Electronic Edition

This paper discusses the contested role of images in electronic editions, and summarizes some of the chief arguments for their inclusion. I then argue that, to truly determine the importance of images to the function of electronic editions, we must understand the contribution the image makes to the form of textual knowledge provided by the edition. I suggest a distinction between editions which are primarily pedagogical in their aims, those which aim above all at scholarly authority, and those which attempt to provide textual information as high-quality data which can be analysed and processed. I conclude that the latter represents the most significant future trend in electronic editing. This revised version was published online in July 2006 with corrections to the Cover Date.     

The As-prepared surfaces of C-axis-oriented Nd1Ba2Cu3Oy thin films characterized using scanning probe microscopes

Recently, superconducting Nd₁Ba₂Cu₃O_y (Ndl23) thin films with high superconducting transition temperature (T _c) have been successfully fabricated at our institute employing the standard laser ablation method. In this paper, we report the results of surface characterization of the Nd123 thin films using an ultrahigh vacuum scanning tunneling microscope/spectroscopy (UHV-STM/STS) and an atomic force microscope (AFM) system operated in air. Clear spiral pattern is observed on the surfaces of Nd123 thin films by STM and AFM, suggesting that films are formed by two-dimensional island growth mode. Contour plots of the spirals show that the step heights of the spirals are not always the integer or half-integer number of thec-axis parameter of the structure. This implies that the surface natural termination layer of the films may not be unique. This result is supported byI-V STS measurements. The surface morphology of the Nd123 thin films is compared with that of thec-axis-oriented Y₁Ba₂Cu₃S_y thin films. Surface atomic images of the as-prepared Nd123 thin films are obtained employing both STM and AFM. STS measurements show that most of the surfaces are semiconductive. The results of STS measurements together with the fact that we are able to see the surface atomic images using scanning probe microscopes suggest that exposure to air does not cause serious degradation to the as-prepared surfaces of Nd123 thin films.     

The use of the scanning electron microscope in the determination of the mineral composition of Ballachulish slate

Slate is a fine-grained, low-grade metamorphic rock derived from argillaceous sediments or occasionally volcanic ash. Although most slates contain mainly quartz, chlorite and white mica, they vary considerably in their durability, some lasting centuries while others fail after a few years of service. A detailed characterisation of their mineralogy is required for the assessment of performance, and to establish the provenance of a used slate. A combination of methods was used to examine Ballachulish slates; XRD analysis to determine the principal minerals present, XRF analysis to determine the total chemical composition, and scanning electron microscopy to determine the chemical composition of individual minerals. It was found that the white mica in Ballachulish slate is phengite and the chlorite is ripidolite. Feldspar is present as albite and carbonate as ferroan dolomite. Several accessory minerals were also identified, including chloritoid, monzonite and zircon. There was considerable variation in the ratio of the principal minerals, making it impossible to identify used slates by this criterion. Instead, chemical composition of the individual minerals, and possibly key accessory minerals, should be used to determine the provenance of slates.     

Martha J. Farah.

Recognizes Martha J. Farah for rigorous empirical and theoretical analysis of visual cognition, in which understanding of normal function and analysis of neurological deficits illuminate and strengthen one another. Applying diverse experimental techniques within an integrated approach to the study of mind and brain, she has sharpened and helped to answer fundamental questions about how humans generate and manipulate visual images, recognize objects, and attend to positions in space. Along with a citation, a biography is presented for Farah, as well as a bibliography of her works. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Probabilistic linear models for multiresolution estimation in gray-level images

A multiresolution analysis of digital gray-level images is presented. A gray-level multi-scale framework is determined from two main assumptions: the gray scale is binary at the finest spatial resolution, and the gray levels of composed regions are obtained additively. In order to interrelate the gray-level histograms of the same image at different resolutions, probabilistic linear models are developed, which are then applied for estimation. Linear-optimization theory is used as a way of constructing such models. A general procedure for image processing is sketched, based on gray-level estimation. A versatile algorithm for nonlinear filtering is derived. Some examples of prospective applications are given.This work was partially supported by grant TIC91-646 from the DGYCIT of the Spanish Government.     

A snake for model-based segmentation of biomedical images

In this work we present a snake based approach for the segmentation of images of computerized tomography (CT) scans. We introduce a new term for the internal energy and another one for external energy which solve common problems associated with classical snakes in this type of images. A simplified minimizing method is also presented.     

Hyperparameter estimation for satellite image restoration using a MCMC maximum-likelihood method

The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ? function, involving two hyperparameters. Our goal is to estimate the optimal parameters in order to automatically reconstruct images. We propose to use the maximum-likelihood estimator (MLE), applied to the observed image. We need sampling from prior and posterior distributions. Since the convolution prevents use of standard samplers, we have developed a modified Geman-Yang algorithm, using an auxiliary variable and a cosine transform. We present a Markov chain Monte Carlo maximum-likelihood (MCMCML) technique which is able to simultaneously achieve the estimation and the reconstruction.     

无人机定位技术及其应用

分析了无人机定位过程及定位原理，着重研究了无人机定位精度，比较了各种定位方法。提出利用无人机定位技术可提高超视距反舰导弹作战能力。