10,246 research outputs found
Edge and Line Feature Extraction Based on Covariance Models
age segmentation based on contour extraction usually involves three stages of image operations: feature extraction, edge detection and edge linking. This paper is devoted to the first stage: a method to design feature extractors used to detect edges from noisy and/or blurred images. The method relies on a model that describes the existence of image discontinuities (e.g. edges) in terms of covariance functions. The feature extractor transforms the input image into a “log-likelihood ratio” image. Such an image is a good starting point of the edge detection stage since it represents a balanced trade-off between signal-to-noise ratio and the ability to resolve detailed structures. For 1-D signals, the performance of the edge detector based on this feature extractor is quantitatively assessed by the so called “average risk measure”. The results are compared with the performances of 1-D edge detectors known from literature. Generalizations to 2-D operators are given. Applications on real world images are presented showing the capability of the covariance model to build edge and line feature extractors. Finally it is shown that the covariance model can be coupled to a MRF-model of edge configurations so as to arrive at a maximum a posteriori estimate of the edges or lines in the image
Maximum likelihood estimation of cloud height from multi-angle satellite imagery
We develop a new estimation technique for recovering depth-of-field from
multiple stereo images. Depth-of-field is estimated by determining the shift in
image location resulting from different camera viewpoints. When this shift is
not divisible by pixel width, the multiple stereo images can be combined to
form a super-resolution image. By modeling this super-resolution image as a
realization of a random field, one can view the recovery of depth as a
likelihood estimation problem. We apply these modeling techniques to the
recovery of cloud height from multiple viewing angles provided by the MISR
instrument on the Terra Satellite. Our efforts are focused on a two layer cloud
ensemble where both layers are relatively planar, the bottom layer is optically
thick and textured, and the top layer is optically thin. Our results
demonstrate that with relative ease, we get comparable estimates to the M2
stereo matcher which is the same algorithm used in the current MISR standard
product (details can be found in [IEEE Transactions on Geoscience and Remote
Sensing 40 (2002) 1547--1559]). Moreover, our techniques provide the
possibility of modeling all of the MISR data in a unified way for cloud height
estimation. Research is underway to extend this framework for fast, quality
global estimates of cloud height.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS243 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images
We present a novel kernel regression framework for smoothing scalar surface
data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel
constructed from the eigenfunctions, we formulate a new bivariate kernel
regression framework as a weighted eigenfunction expansion with the heat kernel
as the weights. The new kernel regression is mathematically equivalent to
isotropic heat diffusion, kernel smoothing and recently popular diffusion
wavelets. Unlike many previous partial differential equation based approaches
involving diffusion, our approach represents the solution of diffusion
analytically, reducing numerical inaccuracy and slow convergence. The numerical
implementation is validated on a unit sphere using spherical harmonics. As an
illustration, we have applied the method in characterizing the localized growth
pattern of mandible surfaces obtained in CT images from subjects between ages 0
and 20 years by regressing the length of displacement vectors with respect to
the template surface.Comment: Accepted in Medical Image Analysi
Kajian motivasi ekstrinsik di antara Pelajar Lepasan Sijil dan Diploma Politeknik Jabatan Kejuruteraan Awam KUiTTHO
Kajian ini dijalankan untuk menyelidiki pengaruh dorongan keluarga, cara pengajaran pensyarah, pengaruh rakan sebaya dan kemudahan infrastruktur terhadap motivasi ekstrinsik bagi pelajar tahun tiga dan tahun empat lepasan sijil dan diploma politeknik Jabatan Kejuruteraan Awain Kolej Universiti Teknologi Tun Hussein Onn. Sampel kajian ini beijumlah 87 orang bagi pelajar lepasan sijil politeknik dan 38 orang bagi lepasan diploma politeknik. Data kajian telah diperolehi melalui borang soal selidik dan telah dianalisis menggunakan perisian SPSS (Statical Package For Sciences). Hasil kajian telah dipersembahkan dalam bentuk jadual dan histohgrapi. Analisis kajian mendapati bahawa kedua-dua kumpulan setuju bahawa faktor-faktor di atas memberi kesan kepada motivasi ekstrinsik mereka. Dengan kata lain faktpr-faktor tersebut penting dalam membentuk pelajar mencapai kecemerlangan akademik
A Comparison of Weak Lensing Measurements From Ground- and Space-Based Facilities
We assess the relative merits of weak lensing surveys, using overlapping
imaging data from the ground-based Subaru telescope and the Hubble Space
Telescope (HST). Our tests complement similar studies undertaken with simulated
data. From observations of 230,000 matched objects in the 2 square degree
COSMOS field, we identify the limit at which faint galaxy shapes can be
reliably measured from the ground. Our ground-based shear catalog achieves
sub-percent calibration bias compared to high resolution space-based data, for
galaxies brighter than i'~24.5 and with half-light radii larger than 1.8". This
selection corresponds to a surface density of ~15 galaxies per sq arcmin
compared to ~71 per sq arcmin from space. On the other hand the survey speed of
current ground-based facilities is much faster than that of HST, although this
gain is mitigated by the increased depth of space-based imaging desirable for
tomographic (3D) analyses. As an independent experiment, we also reconstruct
the projected mass distribution in the COSMOS field using both data sets, and
compare the derived cluster catalogs with those from X-ray observations. The
ground-based catalog achieves a reasonable degree of completeness, with minimal
contamination and no detected bias, for massive clusters at redshifts
0.2<z<0.5. The space-based data provide improved precision and a greater
sensitivity to clusters of lower mass or at higher redshift.Comment: 12 pages, 8 figures, submitted to ApJ, Higher resolution figures
available at http://www.astro.caltech.edu/~mansi/GroundvsSpace.pd
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