Sparse Geometric Super-Resolution

author: Stéphane Mallat, Applied Mathematics - CMAP, École Polytechnique
published: Dec. 5, 2008,   recorded: November 2008,   views: 3686
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Description

What is the maximum signal resolution that can be recovered from partial noisy or degraded data ? This inverse problem is a central issue, from medical to satellite imaging, from geophysical seismic to HDTV visualization of Internet videos. Increasing an image resolution is possible by taking advantage of "geometric regularities", whatever it means. Super-resolution can indeed be achieved for signals having a sparse representation which is "incoherent" relatively to the measurement system.

For images and videos, it requires to construct sparse representations in redundant dictionaries of waveforms, which are adapted to geometric image structures. Signal recovery in redundant dictionaries is discussed, and applications are shown in dictionaries of bandlets for image super-resolution.

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Reviews and comments:

Comment1 Aldo Camargo, December 8, 2008 at 3:18 a.m.:

I think that is a really good information to understand the use of sparce theory in super -resolution.


Comment2 Gaurishankar Kesarwani, March 15, 2010 at 6:59 p.m.:

A wonderful lecture. I have seen it a number of time . It is very infromative . I will thank Dr. Mallat for this lecture.

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