An efficient first-order method for l1 compression of images

We consider the problem of lossy compression of images using sparse representations from overcomplete dictionaries. This problem is in principle easy to solve using standard algorithms for convex programming, but often the large dimensions render such an approach intractable. We present a highly eff...

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Bibliographic Details
Main Authors: Dahl, Joachim, Ostergaard, Jan, Jensen, Tobias Lindstrom, Jensen, Soren Holdt
Format: Conference Proceeding
Language:English
Subjects:
Basis pursuit
convex optimization
Dictionaries
Equations
first-order optimization algorithms
Gradient methods
Image coding
image compression
Image reconstruction
Image restoration
Large-scale systems
Minimization methods
Pursuit algorithms
Signal processing algorithms
sparse approximations
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Summary:We consider the problem of lossy compression of images using sparse representations from overcomplete dictionaries. This problem is in principle easy to solve using standard algorithms for convex programming, but often the large dimensions render such an approach intractable. We present a highly efficient method based on recently developed first-order methods, which enables us to compute sparse approximations of entire images with modest time and memory consumption.
ISSN:1520-6149
DOI:10.1109/ICASSP.2009.4959757