5,780 research outputs found
Self-similar prior and wavelet bases for hidden incompressible turbulent motion
This work is concerned with the ill-posed inverse problem of estimating
turbulent flows from the observation of an image sequence. From a Bayesian
perspective, a divergence-free isotropic fractional Brownian motion (fBm) is
chosen as a prior model for instantaneous turbulent velocity fields. This
self-similar prior characterizes accurately second-order statistics of velocity
fields in incompressible isotropic turbulence. Nevertheless, the associated
maximum a posteriori involves a fractional Laplacian operator which is delicate
to implement in practice. To deal with this issue, we propose to decompose the
divergent-free fBm on well-chosen wavelet bases. As a first alternative, we
propose to design wavelets as whitening filters. We show that these filters are
fractional Laplacian wavelets composed with the Leray projector. As a second
alternative, we use a divergence-free wavelet basis, which takes implicitly
into account the incompressibility constraint arising from physics. Although
the latter decomposition involves correlated wavelet coefficients, we are able
to handle this dependence in practice. Based on these two wavelet
decompositions, we finally provide effective and efficient algorithms to
approach the maximum a posteriori. An intensive numerical evaluation proves the
relevance of the proposed wavelet-based self-similar priors.Comment: SIAM Journal on Imaging Sciences, 201
Coronal Mass Ejection Detection using Wavelets, Curvelets and Ridgelets: Applications for Space Weather Monitoring
Coronal mass ejections (CMEs) are large-scale eruptions of plasma and
magnetic feld that can produce adverse space weather at Earth and other
locations in the Heliosphere. Due to the intrinsic multiscale nature of
features in coronagraph images, wavelet and multiscale image processing
techniques are well suited to enhancing the visibility of CMEs and supressing
noise. However, wavelets are better suited to identifying point-like features,
such as noise or background stars, than to enhancing the visibility of the
curved form of a typical CME front. Higher order multiscale techniques, such as
ridgelets and curvelets, were therefore explored to characterise the morphology
(width, curvature) and kinematics (position, velocity, acceleration) of CMEs.
Curvelets in particular were found to be well suited to characterising CME
properties in a self-consistent manner. Curvelets are thus likely to be of
benefit to autonomous monitoring of CME properties for space weather
applications.Comment: Accepted for publication in Advances in Space Research (3 April 2010
Motion compensation and very low bit rate video coding
Recently, many activities of the International Telecommunication Union (ITU) and the International Standard Organization (ISO) are leading to define new standards for very low bit-rate video coding, such as H.263 and MPEG-4 after successful applications of the international standards H.261 and MPEG-1/2 for video coding above 64kbps. However, at very low bit-rate the classic block matching based DCT video coding scheme suffers seriously from blocking artifacts which degrade the quality of reconstructed video frames considerably. To solve this problem, a new technique in which motion compensation is based on dense motion field is presented in this dissertation.
Four efficient new video coding algorithms based on this new technique for very low bit-rate are proposed. (1) After studying model-based video coding algorithms, we propose an optical flow based video coding algorithm with thresh-olding techniques. A statistic model is established for distribution of intensity difference between two successive frames, and four thresholds are used to control the bit-rate and the quality of reconstructed frames. It outperforms the typical model-based techniques in terms of complexity and quality of reconstructed frames. (2) An efficient algorithm using DCT coded optical flow. It is found that dense motion fields can be modeled as the first order auto-regressive model, and efficiently compressed with DCT technique, hence achieving very low bit-rate and higher visual quality than the H.263/TMN5. (3) A region-based discrete wavelet transform video coding algorithm. This algorithm implements dense motion field and regions are segmented according to their content significance. The DWT is applied to residual images region by region, and bits are adaptively allocated to regions. It improves the visual quality and PSNR of significant regions while maintaining low bit-rate. (4) A segmentation-based video coding algorithm for stereo sequence. A correlation-feedback algorithm with Kalman filter is utilized to improve the accuracy of optical flow fields. Three criteria, which are associated with 3-D information, 2-D connectivity and motion vector fields, respectively, are defined for object segmentation. A chain code is utilized to code the shapes of the segmented objects. it can achieve very high compression ratio up to several thousands
Laser Ultrasound Inspection Based on Wavelet Transform and Data Clustering for Defect Estimation in Metallic Samples
Laser-generated ultrasound is a modern non-destructive testing technique. It has been investigated over recent years as an alternative to classical ultrasonic methods, mainly in industrial maintenance and quality control procedures. In this study, the detection and reconstruction of internal defects in a metallic sample is performed by means of a time-frequency analysis of ultrasonic waves generated by a laser-induced thermal mechanism. In the proposed methodology, we used wavelet transform due to its multi-resolution time frequency characteristics. In order to isolate and estimate the corresponding time of flight of eventual ultrasonic echoes related to internal defects, a density-based spatial clustering was applied to the resulting time frequency maps. Using the laser scan beamâs position, the ultrasonic transducerâs location and the echoesâ arrival times were determined, the estimation of the defectâs position was carried out afterwards. Finally, clustering algorithms were applied to the resulting geometric solutions from the set of the laser scan points which was proposed to obtain a two-dimensional projection of the defect outline over the scan plane. The study demonstrates that the proposed method of wavelet transform ultrasonic imaging can be effectively applied to detect and size internal defects without any reference information, which represents a valuable outcome for various applications in the industry. View Full-TextPeer ReviewedPostprint (published version
Assessment and application of wavelet-based optical flow velocimetry (wOFV) to wall-bounded turbulent flows
The performance of a wavelet-based optical flow velocimetry (wOFV) algorithm
to extract high accuracy and high resolution velocity fields from particle
images in wall-bounded turbulent flows is assessed. wOFV is first evaluated
using synthetic particle images generated from a channel flow DNS of a
turbulent boundary layer. The sensitivity of wOFV to the regularization
parameter (lambda) is quantified and results are compared to PIV. Results on
synthetic particle images indicated different sensitivity to
under-regularization or over-regularization depending on which region of the
boundary layer is analyzed. Synthetic data revealed that wOFV can modestly
outperform PIV in vector accuracy across a broad lambda range. wOFV showed
clear advantages over PIV in resolving the viscous sublayer and obtaining
highly accurate estimates of the wall shear stress. wOFV was also applied to
experimental data of a developing turbulent boundary layer. Overall, wOFV
revealed good agreement with both PIV and PIV + PTV. However, wOFV was able to
successfully resolve the wall shear stress and correctly normalize the boundary
layer streamwise velocity to wall units where PIV and PIV + PTV showed larger
deviations. Analysis of the turbulent velocity fluctuations revealed spurious
results for PIV in close proximity to the wall, leading to significantly
exaggerated and non-physical turbulence intensity. PIV + PTV showed a minor
improvement in this aspect. wOFV did not exhibit this same effect, revealing
that it is more accurate in capturing small-scale turbulent motion in the
vicinity of boundaries. The enhanced vector resolution of wOFV enabled improved
estimation of instantaneous derivative quantities and intricate flow structure
both closer to the wall. These aspects show that, within a reasonable lambda
range, wOFV can improve resolving the turbulent motion occurring in the
vicinity of physical boundaries
An Efficient Algorithm for Video Super-Resolution Based On a Sequential Model
In this work, we propose a novel procedure for video super-resolution, that
is the recovery of a sequence of high-resolution images from its low-resolution
counterpart. Our approach is based on a "sequential" model (i.e., each
high-resolution frame is supposed to be a displaced version of the preceding
one) and considers the use of sparsity-enforcing priors. Both the recovery of
the high-resolution images and the motion fields relating them is tackled. This
leads to a large-dimensional, non-convex and non-smooth problem. We propose an
algorithmic framework to address the latter. Our approach relies on fast
gradient evaluation methods and modern optimization techniques for
non-differentiable/non-convex problems. Unlike some other previous works, we
show that there exists a provably-convergent method with a complexity linear in
the problem dimensions. We assess the proposed optimization method on {several
video benchmarks and emphasize its good performance with respect to the state
of the art.}Comment: 37 pages, SIAM Journal on Imaging Sciences, 201
A Chandra Study of Temperature Substructures in Intermediate-Redshift Galaxy Clusters
By analyzing the gas temperature maps created from the Chandra archive data,
we reveal the prevailing existence of temperature substructures on ~100 kpc
scales in the central regions of nine intermediate-redshift (z~0.1) galaxy
clusters, which resemble those found in the Virgo and Coma Clusters. Each
substructure contains a clump of hot plasma whose temperature is about 2-3 keV
higher than the environment, corresponding to an excess thermal energy of
~1E58-1E60 erg per clump. Since if there were no significant non-gravitational
heating sources, these substructures would have perished in 1E8-1E9 yrs due to
thermal conduction and turbulent flows, whose velocity is found to range from
about 200 to 400 km/s, we conclude that the substructures cannot be created and
sustained by inhomogeneous radiative cooling. We also eliminate the
possibilities that the temperature substructures are caused by supernova
explosions, or by the non-thermal X-ray emission due to the
inverse-Comptonization of the CMB photons. By calculating the rising time of
AGN-induced buoyant bubbles, we speculate that the intermittent AGN outbursts
(~ 1E60 erg per burst) may have played a crucial role in the forming of the
high temperature substructures. Our results are supported by recent study of
McNamara & Nulsen (2007), posing a tight observational constraint on future
theoretical and numerical studies.Comment: 31 pages, 7 figures, ApJ accepte
Time frequency analysis in terahertz pulsed imaging
Recent advances in laser and electro-optical technologies have made the previously under-utilized terahertz frequency band of the electromagnetic spectrum
accessible for practical imaging. Applications are emerging, notably in the biomedical domain. In this chapter the technique of terahertz pulsed imaging is
introduced in some detail. The need for special computer vision methods, which arises from the use of pulses of radiation and the acquisition of a time series at
each pixel, is described. The nature of the data is a challenge since we are interested not only in the frequency composition of the pulses, but also how these differ for different parts of the pulse. Conventional and short-time Fourier transforms and wavelets were used in preliminary experiments on the analysis of terahertz
pulsed imaging data. Measurements of refractive index and absorption coefficient were compared, wavelet compression assessed and image classification by multidimensional
clustering techniques demonstrated. It is shown that the timefrequency methods perform as well as conventional analysis for determining material properties. Wavelet compression gave results that were robust through compressions that used only 20% of the wavelet coefficients. It is concluded that the time-frequency methods hold great promise for optimizing the extraction of the spectroscopic information contained in each terahertz pulse, for the analysis of more complex signals comprising multiple pulses or from recently introduced acquisition techniques
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