Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Noise-Aware Texture-Preserving Low-Light Enhancement   A simple and effective low-light image enhancement method based on a
noise-aware texture-preserving retinex model is proposed in this work. The new
method, called NATLE, attempts to strike a balance between noise removal and
natural texture preservation through a low-complexity solution. Its cost
function includes an estimated piece-wise smooth illumination map and a
noise-free texture-preserving reflectance map. Afterwards, illumination is
adjusted to form the enhanced image together with the reflectance map.
Extensive experiments are conducted on common low-light image enhancement
datasets to demonstrate the superior performance of NATLE.

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The categories of this paper are: astro-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: stat
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The categories of this paper are: plasm-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: hep-ex
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The categories of this paper are: q-fin
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The categories of this paper are: atom-ph
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The categories of this paper are: physics
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The categories of this paper are: dg-ga
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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: supr-con
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The categories of this paper are: q-alg