Automated parameterisation for multi-scale image segmentation on multiple layers

AbstractWe introduce a new automated approach to parameterising multi-scale image segmentation of multiple layers, and we implemented it as a generic tool for the eCognition® software. This approach relies on the potential of the local variance (LV) to detect scale transitions in geospatial data. The tool detects the number of layers added to a project and segments them iteratively with a multiresolution segmentation algorithm in a bottom-up approach, where the scale factor in the segmentation, namely, the scale parameter (SP), increases with a constant increment. The average LV value of the objects in all of the layers is computed and serves as a condition for stopping the iterations: when a scale level records an LV value that is equal to or lower than the previous value, the iteration ends, and the objects segmented in the previous level are retained. Three orders of magnitude of SP lags produce a corresponding number of scale levels. Tests on very high resolution imagery provided satisfactory results for generic applicability. The tool has a significant potential for enabling objectivity and automation of GEOBIA analysis

Distances to Populous Clusters in the LMC via the K-Band Luminosity of the Red Clump

We present results from a study of the distances and distribution of a sample of intermediate-age clusters in the Large Magellanic Cloud. Using deep near-infrared photometry obtained with ISPI on the CTIO 4m, we have measured the apparent K-band magnitude of the core helium burning red clump stars in 17 LMC clusters. We combine cluster ages and metallicities with the work of Grocholski & Sarajedini to predict each cluster's absolute K-band red clump magnitude, and thereby calculate absolute cluster distances. An analysis of these data shows that the cluster distribution is in good agreement with the thick, inclined disk geometry of the LMC, as defined by its field stars. We also find that the old globular clusters follow the same distribution, suggesting that the LMC's disk formed at about the same time as the globular clusters, ~ 13 Gyr ago. Finally, we have used our cluster distances in conjunction with the disk geometry to calculate the distance to the LMC center, for which we find (m-M)o = 18.40 +/- 0.04_{ran} +/- 0.08_{sys}, or Do = 47.9 +/- 0.9 +/- 1.8 kpc.Comment: 31 pages including 5 figures and 7 tables. Accepted for publication in the August 2007 issue of A

Live Imaging of Type I Collagen Assembly Dynamics in Osteoblasts Stably Expressing GFP and mCherry-Tagged Collagen Constructs

Type I collagen is the most abundant extracellular matrix protein in bone and other connective tissues and plays key roles in normal and pathological bone formation as well as in connective tissue disorders and fibrosis. Although much is known about the collagen biosynthetic pathway and its regulatory steps, the mechanisms by which it is assembled extracellularly are less clear. We have generated GFPtpz and mCherry-tagged collagen fusion constructs for live imaging of type I collagen assembly by replacing the α2(I)-procollagen N-terminal propeptide with GFPtpz or mCherry. These novel imaging probes were stably transfected into MLO-A5 osteoblast-like cells and fibronectin-null mouse embryonic fibroblasts (FN-null-MEFs) and used for imaging type I collagen assembly dynamics and its dependence on fibronectin. Both fusion proteins co-precipitated with α1(I)-collagen and remained intracellular without ascorbate but were assembled into α1(I) collagen-containing extracellular fibrils in the presence of ascorbate. Immunogold-EM confirmed their ultrastuctural localization in banded collagen fibrils. Live cell imaging in stably transfected MLO-A5 cells revealed the highly dynamic nature of collagen assembly and showed that during assembly the fibril networks are continually stretched and contracted due to the underlying cell motion. We also observed that cell-generated forces can physically reshape the collagen fibrils. Using co-cultures of mCherry- and GFPtpz-collagen expressing cells, we show that multiple cells contribute collagen to form collagen fiber bundles. Immuno-EM further showed that individual collagen fibrils can receive contributions of collagen from more than one cell. Live cell imaging in FN-null-MEFs expressing GFPtpz-collagen showed that collagen assembly was both dependent upon and dynamically integrated with fibronectin assembly. These GFP-collagen fusion constructs provide a powerful tool for imaging collagen in living cells and have revealed novel and fundamental insights into the dynamic mechanisms for the extracellular assembly of collagen

Spinodal decomposition in alkali feldspar studied by atom probe tomography

We used atom probe tomography to complement electron microscopy for the investigation of spinodal decomposition in alkali feldspar. To this end, gem-quality alkali feldspar of intermediate composition with a mole fraction of aK=0.43 of the K end-member was prepared from Madagascar orthoclase by ion-exchange with (NaK)Cl molten salt. During subsequent annealing at 550∘C and close to ambient pressure the ion-exchanged orthoclase unmixed producing a coherent lamellar intergrowth of Na-rich and K-rich lamellae. The chemical separation was completed, and equilibrium Na–K partitioning between the different lamellae was attained within four days, which was followed by microstructural coarsening. After annealing for 4 days, the wavelength of the lamellar microstructure was ≈17nm and it increased to ≈30nm after annealing for 16 days. The observed equilibrium compositions of the Na-rich and K-rich lamellae are in reasonable agreement with an earlier experimental determination of the coherent solvus. The excess energy associated with compositional gradients at the lamellar interfaces was quantified from the initial wavelength of the lamellar microstructure and the lamellar compositions as obtained from atom probe tomography using the Cahn–Hilliard theory. The capability of atom probe tomography to deliver quantitative chemical compositions at nm resolution opens new perspectives for studying the early stages of exsolution. In particular, it helps to shed light on the phase relations in nm scaled coherent intergrowth

Finding rare objects and building pure samples: Probabilistic quasar classification from low resolution Gaia spectra

We develop and demonstrate a probabilistic method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our expectation (priors) concerning the relative frequencies of different classes of objects. We demonstrate our method using the Discrete Source Classifier, a supervised classifier currently based on Support Vector Machines, which we are developing in preparation for the Gaia data analysis. DSC classifies objects using their very low resolution optical spectra. We look in detail at the problem of quasar classification, because identification of a pure quasar sample is necessary to define the Gaia astrometric reference frame. By varying a posterior probability threshold in DSC we can trade off sample completeness and contamination. We show, using our simulated data, that it is possible to achieve a pure sample of quasars (upper limit on contamination of 1 in 40,000) with a completeness of 65% at magnitudes of G=18.5, and 50% at G=20.0, even when quasars have a frequency of only 1 in every 2000 objects. The star sample completeness is simultaneously 99% with a contamination of 0.7%. Including parallax and proper motion in the classifier barely changes the results. We further show that not accounting for class priors in the target population leads to serious misclassifications and poor predictions for sample completeness and contamination. (Truncated)Comment: MNRAS accepte

The Frequency of Barred Spiral Galaxies in the Near-IR

We have determined the fraction of barred galaxies in the H-band for a statistically well-defined sample of 186 spirals drawn from the Ohio State University Bright Spiral Galaxy survey. We find 56% of our sample to be strongly barred at H, while another 16% is weakly barred. Only 27% of our sample is unbarred in the near-infrared. The RC3 and the Carnegie Atlas of Galaxies both classify only about 30% of our sample as strongly barred. Thus strong bars are nearly twice as prevalent in the near-infrared as in the optical. The frequency of genuine optically hidden bars is significant, but lower than many claims in the literature: 40% of the galaxies in our sample that are classified as unbarred in the RC3 show evidence for a bar in the H-band, while for the Carnegie Atlas this fraction is 66%. Our data reveal no significant trend in bar fraction as a function of morphology in either the optical or H-band. Optical surveys of high redshift galaxies may be strongly biased against finding bars, as bars are increasingly difficult to detect at bluer rest wavelengths.Comment: LaTeX with AASTeX style file, 23 pages with 6 figures. Accepted for publication in The Astronomical Journal (Feb. 2000