Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Generalized Structured Low-Rank Matrix Completion Algorithm for MR
  Image Recovery   Recent theory of mapping an image into a structured low-rank Toeplitz or
Hankel matrix has become an effective method to restore images. In this paper,
we introduce a generalized structured low-rank algorithm to recover images from
their undersampled Fourier coefficients using infimal convolution
regularizations. The image is modeled as the superposition of a piecewise
constant component and a piecewise linear component. The Fourier coefficients
of each component satisfy an annihilation relation, which results in a
structured Toeplitz matrix, respectively. We exploit the low-rank property of
the matrices to formulate a combined regularized optimization problem. In order
to solve the problem efficiently and to avoid the high memory demand resulting
from the large-scale Toeplitz matrices, we introduce a fast and memory
efficient algorithm based on the half-circulant approximation of the Toeplitz
matrix. We demonstrate our algorithm in the context of single and multi-channel
MR images recovery. Numerical experiments indicate that the proposed algorithm
provides improved recovery performance over the state-of-the-art approaches.

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The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
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The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
24
The categories of this paper are: dg-ga
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The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
1
The categories of this paper are: cs