From curvelab@curvelet.org  Fri Apr  1 20:56:51 2005
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Subject: [curvelab-list] CurveLab 1.0 uploaded
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Welcome to the CurveLab list ! CurveLab 1.0 has been uploaded on the
server for testing purposes. Thanks in advance for reporting any bug or
installation problem you might encounter. The 'official' release will be
in about one week, with the tech report explaining the Fast Discrete
Curvelet Transforms.

Let me know if you have any questions.
Thank you for your interest in CurveLab,
Laurent


From demanet@acm.caltech.edu  Wed Jul 13 17:19:32 2005
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Dear Curvelab users,

We have made a few changes to the curvelet.org webpage:

- Uploaded the report 'Fast Discrete Curvelet Transforms', which details
the architecture of both 2D transforms implemented in the software.

- Upgraded to Curvelab 2.0. The main addition is the 3D curvelet 
transform in C++, available in three different implementations: in-core, 
out-of-core and fully MPI-based parallel.

- Uploaded the report '3D Discrete Curvelet Transform'.

- Corrected two bugs in the C++ implementation, related to array sizes for
rectangular images. Thanks to Colin Russell and Jean-Francois Paradis for
pointing this out.

The online user's guide, curvelab.pdf, has also been updated. Please don't
hesitate to send us any feedback you might have at curvelab@curvelet.org.

Yours,
The Curvelab team.




From demanet@acm.caltech.edu  Thu Sep  1 00:16:42 2005
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Dear CurveLab users,

We fixed a compatibility bug in CurveLab 2.0. The C++ code should now
compile with gcc version 4.0. If you are only running the matlab files, or 
if you are using gcc version 3.x, you do not need to download CurveLab 
again.

Thanks to Urs Boeniger for pointing this out.
Cheers,
Laurent and Lexing.


From demanet@acm.caltech.edu  Sun Jun 18 13:54:44 2006
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Dear CurveLab users,

We fixed a few of bugs in CurveLab, related to g++ 4.0. We also corrected
a slight inaccuracy in computing the thresholds in a denoise demo (thanks 
to Gilles Hennenfent for pointing this out). The new version is CurveLab 
2.0.1.

Two sister webpages were recently created, and they should be of interest 
to this email list:

- http://www.l1-magic.org: "L1-MAGIC is a collection of MATLAB routines 
for solving the convex optimization programs central to compressive 
sampling." Compressive sampling (aka compressed sensing) is a method to 
recover sparse data from what appears to be very incomplete measurements.

- http://www.chirplab.org: "ChirpLab is a collection of MATLAB routines 
for the detection of highly oscillatory and nonstationary signals---also 
known as chirps---from very noisy data." ChirpLab is based on wave 
snippets called chirplets.


We welcome any comment related to the CurveLab toolbox. Also, feel free to 
make this email list more lively by submitting paper annoucements related 
to curvelets, etc.

Yours,
Laurent and Lexing
From laurent@math.Stanford.EDU  Fri Jan 26 03:08:19 2007
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Subject: [curvelab-list] Python wrapper and Curvelab 2.0.2
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Dear Curvelab users,

Gilles Hennenfent and Darren Thomson from UBC wrote a Python wrapper for 
Curvelab, called PyCurvelab. They kindly agreed to make it available to 
us.

To use the Python wrapper,

(1) Go to http://www.curvelet.org and upgrade to Curvelab 2.0.2. We had to 
change a few lines in the 2.0.1 code to make it compatible with the 
wrapper. You don't need to upgrade if you won't be using the wrapper. The 
new release is backward compatible.

(2) The weblink to PyCurvelab is listed on the download page of 
curvelet.org.

Thank you Gilles and Darren.

Also, please don't hesitate to use the curvelab-list if you have 
curvelet-related preprints you wish to share with the community---just 
send an email to curvelab-list at acm dot caltech dot edu. The list is 
moderated.

All the best,
The curvelet.org team
From laurent@math.Stanford.EDU  Wed Feb 14 16:49:00 2007
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Subject: [curvelab-list] Curvelets available in Madagascar
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Dear Curvelab users,

Gilles Hennenfent is again making an interesting tool available to the 
community: a Madagascar wrapper for the curvelet transform. See

http://egl.beg.utexas.edu/rsflog/index.php?/archives/126-Curvelet-
transform.html

where you can also see an image denoising experiment. Madagascar is an 
up-and-coming integrated environment for anyone interested in reproducible 
research:

"According to its website (http://rsf.sourceforge.net/), Madagascar 
(formerly known as RSF) is an open-source software package for geophysical 
data processing or, more generally, for reproducible numerical 
experiments. Its mission is to provide

   * a convenient and powerful environment
   * a convenient technology transfer tool

for researchers working with digital image and data processing. The 
machinery is written using Python, SCons, and other tools but the actual 
computation is typically done in C/C++/Fortran although Python, Matlab and 
Mathematica can be employed using APIs provided by Madagascar.More details 
is available on Madagascar website athttp://rsf.sourceforge.net/. There is 
also a Madagascar overview presentation 
(http://rsf.sourceforge.net/rsf_overview.pdf) and a conference extended 
abstract 
(http://slim.eos.ubc.ca/Publications/Public/Conferences/ICASSP/2007/fomel07icassp.pdf) 
that may be of special interest for prospective users."


Enjoy,
The Curvelab team.
From laurent@math.stanford.edu  Fri Aug 24 10:49:02 2007
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From: Laurent Demanet <laurent@math.stanford.edu>
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Subject: [curvelab-list] CurveLab 2.1: curvelets for mirror-extended images
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Dear CurveLab users,

The CurveLab toolbox has been upgraded to version 2.1. We have included a 
version of the curvelet transform that handles image boundaries by mirror 
extension instead of periodization, at a computational complexity 
comparable to the standard FDCT. The result is that boundary curvelets are 
now reflected back into the image, instead of being wrapped around by 
periodicity, in the spirit of wavelets on intervals. Switching to the new 
variant may improve sparsity in cases where the image presents 
strong contrast discontinuities across periodized edges.

A new paper explains the construction of ME curvelets. The Matlab files 
for the new variant are in the directory mecv/. The toolbox can be 
downloaded from

http://www.curvelet.org

A new version of the wave atom transform for mirror-extended images is 
also available. Papers and software on wave atoms are available at the new 
webpage

http://www.waveatom.org

Enjoy, and please report bugs/feedback by email!

Laurent Demanet and Lexing Ying.

From laurent@math.Stanford.EDU  Thu Sep 27 08:35:45 2007
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Dear Curvelab users,

Lexing fixed a small bug related to the inversion of the 3D curvelet 
transform in the case of non-cubic arrays. The new version is CurveLab 
2.1.1.

http://www.curvelet.org/

Cheers,
Laurent
From laurent@math.Stanford.EDU  Thu Nov  1 10:47:23 2007
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From: Laurent Demanet <laurent@math.Stanford.EDU>
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Dear Curvelab users,

Gilles Hennenfent has done great work again:


---------- Forwarded message ----------
Date: Wed, 31 Oct 2007 19:42:38 -0700
From: Gilles Hennenfent <ghennenfent@eos.ubc.ca>
To: laurent Demanet <laurent@math.Stanford.EDU>, lexing@math.utexas.edu
Subject: Curvelet wrapper for Sparco

Hello,

I just wanted to let you know that we recently released Sparco
toolbox for Matlab (http://www.cs.ubc.ca/labs/scl/sparco/). Sparco is
a suite of problems for testing and benchmarking algorithms for
sparse signal reconstruction. It is also an environment for creating
new test problems, and a suite of standard linear operators is
provided (curvelet transform is one of them) from which new problems
can be assembled.

Cheers,
Gilles

-------------------------------------------------------------
Gilles Hennenfent
PhD student
http://wigner.eos.ubc.ca/~hegilles

Seismic Laboratory for Imaging and Modeling
Department of Earth and Ocean Sciences
The University of British Columbia
6339 Stores Road, Vancouver, BC, V6T 1Z4
Phone: +1 713 893 3455
-------------------------------------------------------------

From rbaena@am.ub.es  Tue Feb 26 08:45:21 2008
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Subject: [curvelab-list] Hello, need some help
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Hello,

  I am Roberto Baena, pHD student at the University of Barcelona, Spain.

  My thesis is about synthesis imaging in astronomy. A few weeks ago, I
discovered the curvelet transform and believed its application to the
images I am working with could be very interesting and fruitful. So I
decided to download the CurveLab software and installed in my laptop.

  Now, I am trying to understand the concepts and also trying to apply the
curvelets to my problem. I read the paper "Fast discret Curvelets
transforms", but there are many things that are still confused for me,
many of them avoid me to use the CurveLab soft in practice.

  Excuse me if the following questions are a little trivials but I prefer
to ask before going on with the work with the concepts/theory unclear.
Now I am using the wrapping curvelet transform.

     1º) When I obtain the coefficients 'c' from an image, I am supposed
to access them by c[s][w](i,j), where 's' is the scale, 'w' the wedge
and I guess (i,j) is the position or sample in that wedge.
         Suppose that I would like to create a new image with all the
curves detected. How can I do this? I mean, Do I need to create
's' images, one for each scale?

     2º) To create that image from the coefficients 'c', do I only have to
arrange them in a 2-D matrix?
         I mean, if I have an original image Im, that it is a matrix of
pixels of dimension N1xN2, from where I obtain coefficients
c[s][w](i,j). For obtaining a curve image, is it enough to put in
order the coefficients in a 2-D matrix N1xN2 (or 's' 2-D matrix)?
or are necessary intermediate operations?

     3º) How can I decide the width of the curves to be detected? Is this
the scale?


Well, I apologize again because I am sure the questions seem sillies, but
believe me, from outside and facing the problem for the first time
everything is a little confusing. So I prefer going step by step.

Thank you for your help and looking forward to hearing from somebody :-)

Roberto.


