Not All Areas Are Equal: A Novel Separation-Restoration-Fusion Network for Image Raindrop Removal

Simple item page
dc.contributor.authorRen, Dongdongen_US
dc.contributor.authorLi, Jinbaoen_US
dc.contributor.authorHan, Mengen_US
dc.contributor.authorShu, Mingleien_US
dc.contributor.editorEisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lueen_US
dc.date.accessioned2020-10-29T18:51:09Z
dc.date.available2020-10-29T18:51:09Z
dc.date.issued2020
dc.description.abstractDetecting and removing raindrops from an image while keeping the high quality of image details has attracted tremendous studies, but remains a challenging task due to the inhomogeneity of the degraded region and the complexity of the degraded intensity. In this paper, we get rid of the dependence of deep learning on image-to-image translation and propose a separationrestoration- fusion network for raindrops removal. Our key idea is to recover regions of different damage levels individually, so that each region achieves the optimal recovery result, and finally fuse the recovered areas. In the region restoration module, to complete the restoration of a specific area, we propose a multi-scale feature fusion global information aggregation attention network to achieve global to local information aggregation. Besides, we also design an inside and outside dense connection dilated network, to ensure the fusion of the separated regions and the fine restoration of the image. The qualitatively and quantitatively evaluations are conducted to evaluate our method with the latest existing methods. The result demonstrates that our method outperforms state-of-the-art methods by a large margin on the benchmark datasets in extensive experiments.en_US
dc.description.number7
dc.description.sectionheadersImage Restoration
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.14162
dc.identifier.issn1467-8659
dc.identifier.pages495-505
dc.identifier.urihttps://doi.org/10.1111/cgf.14162
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14162
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectImage processing
dc.titleNot All Areas Are Equal: A Novel Separation-Restoration-Fusion Network for Image Raindrop Removalen_US
Files
Collections
39-Issue 7