12,758 research outputs found
Image Restoration Using Joint Statistical Modeling in Space-Transform Domain
This paper presents a novel strategy for high-fidelity image restoration by
characterizing both local smoothness and nonlocal self-similarity of natural
images in a unified statistical manner. The main contributions are three-folds.
First, from the perspective of image statistics, a joint statistical modeling
(JSM) in an adaptive hybrid space-transform domain is established, which offers
a powerful mechanism of combining local smoothness and nonlocal self-similarity
simultaneously to ensure a more reliable and robust estimation. Second, a new
form of minimization functional for solving image inverse problem is formulated
using JSM under regularization-based framework. Finally, in order to make JSM
tractable and robust, a new Split-Bregman based algorithm is developed to
efficiently solve the above severely underdetermined inverse problem associated
with theoretical proof of convergence. Extensive experiments on image
inpainting, image deblurring and mixed Gaussian plus salt-and-pepper noise
removal applications verify the effectiveness of the proposed algorithm.Comment: 14 pages, 18 figures, 7 Tables, to be published in IEEE Transactions
on Circuits System and Video Technology (TCSVT). High resolution pdf version
and Code can be found at: http://idm.pku.edu.cn/staff/zhangjian/IRJSM
A Non-Local Structure Tensor Based Approach for Multicomponent Image Recovery Problems
Non-Local Total Variation (NLTV) has emerged as a useful tool in variational
methods for image recovery problems. In this paper, we extend the NLTV-based
regularization to multicomponent images by taking advantage of the Structure
Tensor (ST) resulting from the gradient of a multicomponent image. The proposed
approach allows us to penalize the non-local variations, jointly for the
different components, through various matrix norms with .
To facilitate the choice of the hyper-parameters, we adopt a constrained convex
optimization approach in which we minimize the data fidelity term subject to a
constraint involving the ST-NLTV regularization. The resulting convex
optimization problem is solved with a novel epigraphical projection method.
This formulation can be efficiently implemented thanks to the flexibility
offered by recent primal-dual proximal algorithms. Experiments are carried out
for multispectral and hyperspectral images. The results demonstrate the
interest of introducing a non-local structure tensor regularization and show
that the proposed approach leads to significant improvements in terms of
convergence speed over current state-of-the-art methods
Depth Super-Resolution Meets Uncalibrated Photometric Stereo
A novel depth super-resolution approach for RGB-D sensors is presented. It
disambiguates depth super-resolution through high-resolution photometric clues
and, symmetrically, it disambiguates uncalibrated photometric stereo through
low-resolution depth cues. To this end, an RGB-D sequence is acquired from the
same viewing angle, while illuminating the scene from various uncalibrated
directions. This sequence is handled by a variational framework which fits
high-resolution shape and reflectance, as well as lighting, to both the
low-resolution depth measurements and the high-resolution RGB ones. The key
novelty consists in a new PDE-based photometric stereo regularizer which
implicitly ensures surface regularity. This allows to carry out depth
super-resolution in a purely data-driven manner, without the need for any
ad-hoc prior or material calibration. Real-world experiments are carried out
using an out-of-the-box RGB-D sensor and a hand-held LED light source.Comment: International Conference on Computer Vision (ICCV) Workshop, 201
On the Enhanced Interstellar Scattering Toward B1849+005
(Abridged) This paper reports new Very Large Array (VLA) and Very Long
Baseline Array (VLBA) observations of the extragalactic source B1849+005 at
frequencies between 0.33 and 15 GHz and the re-analysis of archival VLA
observations at 0.33, 1.5, and 4.9 GHz. The structure of this source is complex
but interstellar scattering dominates the structure of the central component at
least to 15 GHz. An analysis of the phase structure functions of the
interferometric visibilities shows the density fluctuations along this line of
sight to be anisotropic (axial ratio = 1.3) with a frequency-independent
position angle, and having an inner scale of roughly a few hundred kilometers.
The anisotropies occur on length scales of order 10^{15} cm (D/5 kpc), which
within the context of certain magnetohydrodynamic turbulence theories indicates
the length scale on which the kinetic and magnetic energy densities are
comparable. A conservative upper limit on the velocity of the scattering
material is 1800 km/s. In the 0.33 GHz field of view, there are a number of
other sources that might also be heavily scattered. Both B1849+005 and PSR
B1849+00 are highly scattered, and they are separated by only 13'. If the lines
of sight are affected by the same ``clump'' of scattering material, it must be
at least 2.3 kpc distant. However, a detailed attempt to account for the
scattering observables toward these sources does not produce a self-consistent
set of parameters for such a clump. A clump of H\alpha emission, possibly
associated with the H II region G33.418-0.004, lies between these two lines of
sight, but it seems unable to account for all of the required excess
scattering.Comment: 23 pages, LaTeX2e AASTeX, 13 figures in 14 PostScript files, accepted
for publication in Ap
Multiscale Phenomenology of the Cosmic Web
We analyze the structure and connectivity of the distinct morphologies that
define the Cosmic Web. With the help of our Multiscale Morphology Filter (MMF),
we dissect the matter distribution of a cosmological CDM N-body
computer simulation into cluster, filaments and walls. The MMF is ideally
suited to adress both the anisotropic morphological character of filaments and
sheets, as well as the multiscale nature of the hierarchically evolved cosmic
matter distribution. The results of our study may be summarized as follows:
i).- While all morphologies occupy a roughly well defined range in density,
this alone is not sufficient to differentiate between them given their overlap.
Environment defined only in terms of density fails to incorporate the intrinsic
dynamics of each morphology. This plays an important role in both linear and
non linear interactions between haloes. ii).- Most of the mass in the Universe
is concentrated in filaments, narrowly followed by clusters. In terms of
volume, clusters only represent a minute fraction, and filaments not more than
9%. Walls are relatively inconspicous in terms of mass and volume. iii).- On
average, massive clusters are connected to more filaments than low mass
clusters. Clusters with M h have on average
two connecting filaments, while clusters with M
h have on average five connecting filaments. iv).- Density profiles
indicate that the typical width of filaments is 2\Mpch. Walls have less well
defined boundaries with widths between 5-8 Mpc h. In their interior,
filaments have a power-law density profile with slope ,
corresponding to an isothermal density profile.Comment: 28 pages, 22 figures, accepted for publication in MNRAS. For a
high-res version see http://www.astro.rug.nl/~weygaert/webmorph_mmf.pd
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