581 research outputs found
ShearLab: A Rational Design of a Digital Parabolic Scaling Algorithm
Multivariate problems are typically governed by anisotropic features such as
edges in images. A common bracket of most of the various directional
representation systems which have been proposed to deliver sparse
approximations of such features is the utilization of parabolic scaling. One
prominent example is the shearlet system. Our objective in this paper is
three-fold: We firstly develop a digital shearlet theory which is rationally
designed in the sense that it is the digitization of the existing shearlet
theory for continuous data. This implicates that shearlet theory provides a
unified treatment of both the continuum and digital realm. Secondly, we analyze
the utilization of pseudo-polar grids and the pseudo-polar Fourier transform
for digital implementations of parabolic scaling algorithms. We derive an
isometric pseudo-polar Fourier transform by careful weighting of the
pseudo-polar grid, allowing exploitation of its adjoint for the inverse
transform. This leads to a digital implementation of the shearlet transform; an
accompanying Matlab toolbox called ShearLab is provided. And, thirdly, we
introduce various quantitative measures for digital parabolic scaling
algorithms in general, allowing one to tune parameters and objectively improve
the implementation as well as compare different directional transform
implementations. The usefulness of such measures is exemplarily demonstrated
for the digital shearlet transform.Comment: submitted to SIAM J. Multiscale Model. Simu
ShearLab 3D: Faithful Digital Shearlet Transforms based on Compactly Supported Shearlets
Wavelets and their associated transforms are highly efficient when
approximating and analyzing one-dimensional signals. However, multivariate
signals such as images or videos typically exhibit curvilinear singularities,
which wavelets are provably deficient of sparsely approximating and also of
analyzing in the sense of, for instance, detecting their direction. Shearlets
are a directional representation system extending the wavelet framework, which
overcomes those deficiencies. Similar to wavelets, shearlets allow a faithful
implementation and fast associated transforms. In this paper, we will introduce
a comprehensive carefully documented software package coined ShearLab 3D
(www.ShearLab.org) and discuss its algorithmic details. This package provides
MATLAB code for a novel faithful algorithmic realization of the 2D and 3D
shearlet transform (and their inverses) associated with compactly supported
universal shearlet systems incorporating the option of using CUDA. We will
present extensive numerical experiments in 2D and 3D concerning denoising,
inpainting, and feature extraction, comparing the performance of ShearLab 3D
with similar transform-based algorithms such as curvelets, contourlets, or
surfacelets. In the spirit of reproducible reseaerch, all scripts are
accessible on www.ShearLab.org.Comment: There is another shearlet software package
(http://www.mathematik.uni-kl.de/imagepro/members/haeuser/ffst/) by S.
H\"auser and G. Steidl. We will include this in a revisio
Scale Invariant Interest Points with Shearlets
Shearlets are a relatively new directional multi-scale framework for signal
analysis, which have been shown effective to enhance signal discontinuities
such as edges and corners at multiple scales. In this work we address the
problem of detecting and describing blob-like features in the shearlets
framework. We derive a measure which is very effective for blob detection and
closely related to the Laplacian of Gaussian. We demonstrate the measure
satisfies the perfect scale invariance property in the continuous case. In the
discrete setting, we derive algorithms for blob detection and keypoint
description. Finally, we provide qualitative justifications of our findings as
well as a quantitative evaluation on benchmark data. We also report an
experimental evidence that our method is very suitable to deal with compressed
and noisy images, thanks to the sparsity property of shearlets
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