Resolving depth measurement ambiguity with commercially available range imaging cameras

Time-of-flight range imaging is typically performed with the amplitude modulated continuous wave method. This involves illuminating a scene with amplitude modulated light. Reflected light from the scene is received by the sensor with the range to the scene encoded as a phase delay of the modulation envelope. Due to the cyclic nature of phase, an ambiguity in the measured range occurs every half wavelength in distance, thereby limiting the maximum useable range of the camera. This paper proposes a procedure to resolve depth ambiguity using software post processing. First, the range data is processed to segment the scene into separate objects. The average intensity of each object can then be used to determine which pixels are beyond the non-ambiguous range. The results demonstrate that depth ambiguity can be resolved for various scenes using only the available depth and intensity information. This proposed method reduces the sensitivity to objects with very high and very low reflectance, normally a key problem with basic threshold approaches. This approach is very flexible as it can be used with any range imaging camera. Furthermore, capture time is not extended, keeping the artifacts caused by moving objects at a minimum. This makes it suitable for applications such as robot vision where the camera may be moving during captures. The key limitation of the method is its inability to distinguish between two overlapping objects that are separated by a distance of exactly one non-ambiguous range. Overall the reliability of this method is higher than the basic threshold approach, but not as high as the multiple frequency method of resolving ambiguity

Temperature structure of the intergalactic medium within seven nearby and bright clusters of galaxies observed with XMM-Newton

Aims. We map the temperature structure of the intra-cluster medium (ICM) within a nearly complete X-ray flux limited sample of galaxy clusters in the redshift range z=[0.045,0.096]. Our sample contains seven bright clusters of galaxies observed with XMM-Newton: Abell 399, Abell 401, Abell 478, Abell 1795, Abell 2029, Abell 2065, Abell 2256. Methods. We use a multi-scale spectral mapping algorithm especially designed to map spectroscopic observables from X-ray extended emission of the ICM. Derived from a former algorithm using Haar wavelets, our algorithm is now implemented with B-spline wavelets in order to perform a more regular analysis of the signal. Results. For the four clusters in our sample that are major mergers, we find a complex thermal structure with strong thermal variations consistent with their dynamics. For two of them, A2065 and A2256, we perform a 3-d analysis of cold front features evidenced from the gas temperature and brightness maps. Furthermore, we detect a significant non-radial thermal structure outside the cool core region of the other 3 more "regular" clusters, with relative amplitudes of about about 10%. We investigate possible implications of this structure on the mass estimates of the "regular" clusters A1795 and A2029, by extracting surface brightness and temperature profiles from sectors correspondings to the hottest and coldest regions in the maps. While compensating with surface brightness for A2029, leading to consistent mass profiles, the temperature structure leads to significant mass discrepancies in the innermost region of A1795.Comment: published in A&

Scaling laws governing stochastic growth and division of single bacterial cells

Uncovering the quantitative laws that govern the growth and division of single cells remains a major challenge. Using a unique combination of technologies that yields unprecedented statistical precision, we find that the sizes of individual Caulobacter crescentus cells increase exponentially in time. We also establish that they divide upon reaching a critical multiple ($\approx$1.8) of their initial sizes, rather than an absolute size. We show that when the temperature is varied, the growth and division timescales scale proportionally with each other over the physiological temperature range. Strikingly, the cell-size and division-time distributions can both be rescaled by their mean values such that the condition-specific distributions collapse to universal curves. We account for these observations with a minimal stochastic model that is based on an autocatalytic cycle. It predicts the scalings, as well as specific functional forms for the universal curves. Our experimental and theoretical analysis reveals a simple physical principle governing these complex biological processes: a single temperature-dependent scale of cellular time governs the stochastic dynamics of growth and division in balanced growth conditions.Comment: Text+Supplementar

Achieving the Way for Automated Segmentation of Nuclei in Cancer Tissue Images through Morphology-Based Approach: a Quantitative Evaluation

In this paper we address the problem of nuclear segmentation in cancer tissue images, that is critical for specific protein activity quantification and for cancer diagnosis and therapy. We present a fully automated morphology-based technique able to perform accurate nuclear segmentations in images with heterogeneous staining and multiple tissue layers and we compare it with an alternate semi-automated method based on a well established segmentation approach, namely active contours. We discuss active contours’ limitations in the segmentation of immunohistochemical images and we demonstrate and motivate through extensive experiments the better accuracy of our fully automated approach compared to various active contours implementations

Persistent Homology in Sparse Regression and its Application to Brain Morphometry

Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system. In this paper, by treating the the tuning parameter as an additional dimension, persistent homological structures over the parameter space is introduced and explored. The structures are then further exploited in speeding up the computation using the proposed soft-thresholding technique. The topological structures are further used as multivariate features in the tensor-based morphometry (TBM) in characterizing white matter alterations in children who have experienced severe early life stress and maltreatment. These analyses reveal that stress-exposed children exhibit more diffuse anatomical organization across the whole white matter region.Comment: submitted to IEEE Transactions on Medical Imagin

Accurate measurement of absolute experimental inelastic mean free paths and EELS differential cross-sections

Methods are described for measuring accurate absolute experimental inelastic mean free paths and differential cross-sections using DualEELS. The methods remove the effects of surface layers and give the results for the bulk materials. The materials used are VC0.83,TiC0.98,VN0.97and TiN0.88but the method should be applicable to a wide range of materials. The data were taken at 200 keVusing a probe half angle of 29mradand a collection angle of 36mrad. The background can be subtracted from under the ionisation edges, which can then be separated from each other. This is achieved by scaling Hartree-Slater calculated cross-sections to the edges in the atomic regions well above the threshold. The average scaling factors required are 1.00 for the non-metal K-edges and 1.01 for the metal L-edges (with uncertainties of a few per cent). If preliminary measurements of the chromatic effects in the post-specimen lenses are correct, both drop to 0.99. The inelastic mean free path for TiC0.98 was measured as 103.6±0.5 nm compared to the prediction of 126.9 nm based on the widely used Iakoubovskii parameterisation

Horizontal flow fields observed in Hinode G-band images IV. Statistical properties of the dynamical environment around pores

The extensive database of high-resolution G-band images observed with the Hinode/SOT is a unique resource to derive statistical properties of pores using advanced digital image processing techniques. The study is based on two data sets: (1) Photometric and morphological properties inferred from single G-band images cover almost seven years from 2006 October 25 to 2013 August 31. (2) Horizontal flow fields have been derived from 356 one-hour sequences of G-band images using LCT for a shorter period of time from 2006 November 3 to 2008 January 6 comprising 13 active regions. A total of 7643/2863 (single/time-averaged) pores builds the foundation of the statistical analysis. Pores are preferentially observed at low latitudes in the southern hemisphere during the deep minimum of solar cycle No. 23. This imbalance reverses during the rise of cycle No. 24, when the pores migrate from high to low latitudes. Pores are rarely encountered in quiet-Sun G-band images, and only about 10% of pores exists in isolation. In general, pores do not exhibit a circular shape. Typical aspect ratios of the semi-major and -minor axes are 3:2 when ellipses are fitted to pores. Smaller pores (more than two-thirds are smaller than 5~Mm^2) tend to be more circular, and their boundaries are less corrugated. Both area and perimeter length of pores obey log-normal frequency distributions. The frequency distribution of the intensity can be reproduced by two Gaussians representing dark and bright components. Bright features resembling umbral dots and even light-bridges cover about 20% of the pore's area. Averaged radial profiles show a peak of the intensity at normalized radius R_N = r /R_pore = 2.1, followed by maxima of the divergence at R_N= 2.3 and the radial component of the horizontal velocity at R_N= 4.6. The divergence is negative within pores.Comment: 14 pages, 13 figures, Accepted for publication in Astronomy and Astrophysic