LoL dataset [@wei2018deep]. Our method reproduces image that is visually closer to the ground-truth in terms of brightness and global contrast.[]{data-label="Fig:qual_lol"}](Images/Enhancement/lol_images/lol_retx "fig:"){width="24.40000%"}
                                                                                                                                                     Input image                                                                                                                                                                                                                                                                                                  LIME [@guo2016lime]                                                                                                                                                                                                                                                                                               CRM [@ying2017bio]                                                                                                                                                                                                                                                                                           Retinex-Net [@wei2018deep]
     ![Visual comparison of low-light enhancement approaches on the LoL dataset [@wei2018deep]. Our method reproduces image that is visually closer to the ground-truth in terms of brightness and global contrast.[]{data-label="Fig:qual_lol"}](Images/Enhancement/lol_images/srie "fig:"){width="24.40000%"}      ![Visual comparison of low-light enhancement approaches on the LoL dataset [@wei2018deep]. Our method reproduces image that is visually closer to the ground-truth in terms of brightness and global contrast.[]{data-label="Fig:qual_lol"}](Images/Enhancement/lol_images/lol_kind "fig:"){width="24.40000%"}   ![Visual comparison of low-light enhancement approaches on the LoL dataset [@wei2018deep]. Our method reproduces image that is visually closer to the ground-truth in terms of brightness and global contrast.[]{data-label="Fig:qual_lol"}](Images/Enhancement/lol_images/lol_ours "fig:"){width="24.40000%"}    ![Visual comparison of low-light enhancement approaches on the LoL dataset [@wei2018deep]. Our method reproduces image that is visually closer to the ground-truth in terms of brightness and global contrast.[]{data-label="Fig:qual_lol"}](Images/Enhancement/lol_images/lol_gt "fig:"){width="24.40000%"}
                                                                                                                                               SRIE [@fu2016weighted]                                                                                                                                                                                                                                                                                          KinD [@zhang2019kindling]                                                                                                                                                                                                                                                                                              MIRNet (Ours)                                                                                                                                                                                                                                                                                                     Ground-truth
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    ![Visual results of image enhancement on the MIT-Adobe FiveK [@mit_fivek] dataset. Compared to the state-of-the-art, our MIRNet makes better color and contrast adjustments and produces image that is vivid, natural and pleasant in appearance. ](Images/Enhancement/fivek/input "fig:"){width="32.40000%"}    