CALL FOR PAPERS

Sampling Theory in Signal and Image Processing

Special Issue on Compressed Sensing

The research field of Compressed Sensing (CS) is new and very rapidly growing. CS is a sampling paradigm that allows us to go beyond the Shannon limit by exploiting the sparsity structure of the signal. CS allows us to capture and represent compressible signals at a rate significantly below the Nyquist rate. The sampling step is very fast since it employs non-adaptive linear projections that preserve the structure of the signal. The signal is reconstructed from these projections by viewing the decoding step as a linear inverse problem that is cast as a sparsity-regularized convex optimization problem.

This special issue is a call to gather a broad range of methods, algorithms and theoretical results in the area of compressed sensing. The retained papers will present new works and review papers. Original contributions are solicited from the following non-exhaustive list of topics:

    Modeling of natural signals and images based on sparse representation.

    Theoretical breakthroughs to assess the sparsity of representations or to ensure the recovery of signals..

    Study of the large scale optimization problems occurring in sparse recovery, with theoretical or algorithmic contributions.

    Applications in medical and biomedical imaging, distributed and remote sensing, astronomical imaging, seismic imaging, analogue to digital information conversion, audio signal processing, video, etc..

Submission Procedure
Prospective authors should follow the typesetting instructions available at http://stsip.org/ and submit the manuscripts to the guest editors. The manuscripts will undergo a standard peer review process according to the following timetable:

    Call for papers September 22, 2009

    Manuscript submissions due: January 15, 2010

    First review completed: April 2, 2010

    Revised manuscripts due: June 4, 2010

    Second review completed: July 16, 2010

    Final manuscript due: September 17, 2010

Guest Editors
Dr. Jean-Luc Starck, Service d'Astrophysique CEA/Saclay France, jstarck (atmark) cea.fr
Dr. Jalal Fadili, GREYC CNRS Caen, Jalal.Fadili (atmark) greyc.ensicaen.fr

This Call for papers in PDF for printing.

	Modeling of natural signals and images based on sparse representation.
	Theoretical breakthroughs to assess the sparsity of representations or to ensure the recovery of signals..
	Study of the large scale optimization problems occurring in sparse recovery, with theoretical or algorithmic contributions.
	Applications in medical and biomedical imaging, distributed and remote sensing, astronomical imaging, seismic imaging, analogue to digital information conversion, audio signal processing, video, etc..

	Call for papers	September 22, 2009
	Manuscript submissions due:	January 15, 2010
	First review completed:	April 2, 2010
	Revised manuscripts due:	June 4, 2010
	Second review completed:	July 16, 2010
	Final manuscript due:	September 17, 2010