Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Real-time $\ell^1$ -- $\ell^2$ deblurring using wavelet expansions of
  operators   Image deblurring is a fundamental problem in imaging, usually solved with
com-putationally intensive optimization procedures. We show that the
minimization can be significantly accelerated by leveraging the fact that
images and blur operators are compressible in the same orthogonal wavelet
basis. The proposed methodology consists of three ingredients: i) a sparse
approximation of the blur operator in wavelet bases, ii) a diagonal
preconditioner and iii) an implementation on massively parallel architectures.
Combing the three ingredients leads to acceleration factors ranging from 30 to
250 on a typical workstation. For instance, a 1024 x 1024 image can be
deblurred in 0.15 seconds, which corresponds to real-time.

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The categories of this paper are: hep-lat
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The categories of this paper are: math-ph
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The categories of this paper are: acc-phys
1
The categories of this paper are: cs
4
The categories of this paper are: cond-mat
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The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
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The categories of this paper are: plasm-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: chao-dyn
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The categories of this paper are: funct-an
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The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an