Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Correlation-based Initialization Algorithm for Tensor-based HSI
  Compression Methods   Tensor decomposition (TD) is widely used in hyperspectral image (HSI)
compression. The initialization of factor matrix in tensor decomposition can
determine the HSI compression performance. It is worth noting that HSI is
highly correlated in bands. However, this phenomenon is ignored by the previous
TD method. Aiming at improving the HSI compression performance, we propose a
method called correlation-based TD initialization algorithm. As HSI is well
approximated by means of a reference band. In accordance with the SVD result of
the reference band, the initialized factor matrices of TD are produced. We
compare our methods with random and SVD-based initialization methods. The
experimental results reveal that our correlation-based TD initialization method
is capable of significantly reducing the computational cost of TD while keeping
the initialization quality and compression performance.

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The categories of this paper are: cond-mat
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The categories of this paper are: funct-an
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The categories of this paper are: physics
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The categories of this paper are: supr-con
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The categories of this paper are: ao-sci
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The categories of this paper are: econ
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The categories of this paper are: nucl-th
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The categories of this paper are: nlin
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The categories of this paper are: cmp-lg
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The categories of this paper are: bayes-an
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: solv-int
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The categories of this paper are: hep-th
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The categories of this paper are: adap-org
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The categories of this paper are: astro-ph