Enhancing Low-Light Color Image via <italic>L</italic><sub>0</sub> Regularization and Reweighted Group Sparsity

Enhancing Low-Light Color Image via <italic>L</italic><sub>0</sub> Regularization and Reweighted Group Sparsity

Classic Retinex model based low-light image enhancement methods ignored the interference of noise, which causes annoying artifacts. In this paper, we propose to estimate the illumination, reflectance and suppress the noise in a whole framework. Instead of using the <inline-formula> <tex-mat...

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Bibliographic Details
Main Authors: Qiang Song, Hangfan Liu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Low-light image enhancement
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">L</italic>₀ sparsity
reweighted group sparsity
noise model
Online Access:https://ieeexplore.ieee.org/document/9489269/

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https://ieeexplore.ieee.org/document/9489269/

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