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Computer Science > Computer Vision and Pattern Recognition
Title: Low-light Enhancement Method Based on Attention Map Net
(Submitted on 19 Aug 2022 (v1), last revised 16 Mar 2023 (this version, v2))
Abstract: Low-light image enhancement is a crucial preprocessing task for some complex vision tasks. Target detection, image segmentation, and image recognition outcomes are all directly impacted by the impact of image enhancement. However, the majority of the currently used image enhancement techniques do not produce satisfactory outcomes, and these enhanced networks have relatively weak robustness. We suggest an improved network called BrightenNet that uses U-Net as its primary structure and incorporates a number of different attention mechanisms as a solution to this issue. In a specific application, we employ the network as the generator and LSGAN as the training framework to achieve better enhancement results. We demonstrate the validity of the proposed network BrightenNet in the experiments that follow in this paper. The results it produced can both preserve image details and conform to human vision standards.
Submission history
From: Mengfei Wu [view email][v1] Fri, 19 Aug 2022 13:18:35 GMT (1151kb)
[v2] Thu, 16 Mar 2023 17:34:15 GMT (0kb,I)
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