{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T20:23:04Z","timestamp":1774038184354,"version":"3.50.1"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62171303"],"award-info":[{"award-number":["62171303"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.knosys.2026.115626","type":"journal-article","created":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T22:50:30Z","timestamp":1772405430000},"page":"115626","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["GSGM : Gradient space guidance method for single-image visible watermark removal"],"prefix":"10.1016","volume":"339","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-9669-395X","authenticated-orcid":false,"given":"Bin","family":"Meng","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6864-9509","authenticated-orcid":false,"given":"Jiliu","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8573-5287","authenticated-orcid":false,"given":"Haoran","family":"Yang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5605-3695","authenticated-orcid":false,"given":"Jiayong","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2975-4976","authenticated-orcid":false,"given":"Yifei","family":"Pu","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.knosys.2026.115626_bib0001","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2026.115626_bib0002","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"The unreasonable effectiveness of deep features as a perceptual metric","author":"Zhang","year":"2018"},{"key":"10.1016\/j.knosys.2026.115626_bib0003","series-title":"Proceedings IEEE International Conference on Multimedia Computing and Systems","first-page":"568","article-title":"Adaptive visible watermarking of images","volume":"1","author":"Kankanhalli","year":"1999"},{"key":"10.1016\/j.knosys.2026.115626_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2025.109999","article-title":"Reversible adversarial visible image watermarking","volume":"234","author":"Xie","year":"2025","journal-title":"Signal Process."},{"key":"10.1016\/j.knosys.2026.115626_bib0005","series-title":"Proceedings of International Conference on Image Processing","first-page":"680","article-title":"An invisible watermarking technique for image verification","volume":"2","author":"Yeung","year":"1997"},{"key":"10.1016\/j.knosys.2026.115626_bib0006","series-title":"2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)","first-page":"909","article-title":"InvisMark: invisible and robust watermarking for AI-generated image provenance","author":"Xu","year":"2025"},{"key":"10.1016\/j.knosys.2026.115626_bib0007","series-title":"Proceedings of 3rd IEEE International Conference on Image Processing","first-page":"211","article-title":"Transparent robust image watermarking","volume":"3","author":"Swanson","year":"1996"},{"key":"10.1016\/j.knosys.2026.115626_bib0008","first-page":"1","article-title":"Robust watermarking based on multi-layer watermark feature fusion","author":"Wu","year":"2025","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.knosys.2026.115626_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.110494","article-title":"ECH3OA: an enhanced Chimp-Harris Hawks optimization algorithm for copyright protection in color images using watermarking techniques","volume":"269","author":"Fahmy","year":"2023","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.knosys.2026.115626_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111971","article-title":"Statistical learning based blind image watermarking approach","volume":"297","author":"Peng","year":"2024","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.knosys.2026.115626_bib0011","series-title":"Proceedings of the 10th ACM Workshop on Multimedia and Security","first-page":"215-220","article-title":"A regression-based restoration technique for automated watermark removal","author":"Westfeld","year":"2008"},{"key":"10.1016\/j.knosys.2026.115626_bib0012","series-title":"Proceedings of the 29th ACM International Conference on Multimedia","first-page":"4426-4434","article-title":"Visible watermark removal via self-calibrated localization and background refinement","author":"Liang","year":"2021"},{"issue":"2","key":"10.1016\/j.knosys.2026.115626_bib0013","first-page":"2411","article-title":"DENet: disentangled embedding network for visible watermark removal","volume":"37","author":"Sun","year":"2023","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"issue":"8","key":"10.1016\/j.knosys.2026.115626_bib0014","doi-asserted-by":"crossref","first-page":"7566","DOI":"10.1109\/TCSVT.2024.3375831","article-title":"A self-supervised CNN for image watermark removal","volume":"34","author":"Tian","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"4","key":"10.1016\/j.knosys.2026.115626_bib0015","first-page":"2983","article-title":"Removing interference and recovering content imaginatively for visible watermark removal","volume":"38","author":"Leng","year":"2024","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.knosys.2026.115626_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106853","article-title":"A unified noise and watermark removal from information bottleneck-based modeling","volume":"181","author":"Huang","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.knosys.2026.115626_bib0017","series-title":"Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques","first-page":"417-424","article-title":"Image inpainting","author":"Bertalmio","year":"2000"},{"key":"10.1016\/j.knosys.2026.115626_bib0018","series-title":"Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)","first-page":"7986","article-title":"Large-scale text-to-image model with inpainting is a zero-shot subject-driven image generator","author":"Shin","year":"2025"},{"key":"10.1016\/j.knosys.2026.115626_bib0019","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"11461","article-title":"RePaint: inpainting using denoising diffusion probabilistic models","author":"Lugmayr","year":"2022"},{"issue":"2","key":"10.1016\/j.knosys.2026.115626_bib0020","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1109\/TPAMI.1980.4766994","article-title":"Digital image enhancement and noise filtering by use of local statistics","volume":"PAMI-2","author":"Lee","year":"1980","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.knosys.2026.115626_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111320","article-title":"CFNet: conditional filter learning with dynamic noise estimation for real image denoising","volume":"284","author":"Zuo","year":"2024","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.knosys.2026.115626_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111973","article-title":"Efficient blind super-resolution imaging via adaptive degradation-aware estimation","volume":"297","author":"Yang","year":"2024","journal-title":"Knowl. Based Syst."},{"issue":"21","key":"10.1016\/j.knosys.2026.115626_bib0023","doi-asserted-by":"crossref","first-page":"4644","DOI":"10.1364\/AO.28.004644","article-title":"Optical symbolic substitution: edge detection using prewitt, sobel, and roberts operators","volume":"28","author":"Cherri","year":"1989","journal-title":"Appl. Opt."},{"key":"10.1016\/j.knosys.2026.115626_bib0024","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Structure-preserving super resolution with gradient guidance","author":"Ma","year":"2020"},{"key":"10.1016\/j.knosys.2026.115626_bib0025","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s11554-021-01083-1","article-title":"Gradient information distillation network for real-time single-image super-resolution","volume":"18","author":"Meng","year":"2021","journal-title":"J. Real-Time Image Process."},{"issue":"1","key":"10.1016\/j.knosys.2026.115626_bib0026","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s00530-021-00838-x","article-title":"FPPN: fast pixel purification network for single-image super-resolution","volume":"28","author":"Meng","year":"2022","journal-title":"Multimed. Syst."},{"key":"10.1016\/j.knosys.2026.115626_bib0027","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.neucom.2020.06.093","article-title":"Gradient-based discriminative modeling for blind image deblurring","volume":"413","author":"Shao","year":"2020","journal-title":"Neurocomputing"},{"key":"10.1016\/j.knosys.2026.115626_bib0028","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2018"},{"key":"10.1016\/j.knosys.2026.115626_bib0029","series-title":"Computer Vision - ECCV 2018: 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part VII","first-page":"3-19","article-title":"CBAM: convolutional block attention module","author":"Woo","year":"2018"},{"key":"10.1016\/j.knosys.2026.115626_bib0030","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"ECA-Net: efficient channel attention for deep convolutional neural networks","author":"Wang","year":"2020"},{"key":"10.1016\/j.knosys.2026.115626_bib0031","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Pyramid feature attention network for saliency detection","author":"Zhao","year":"2019"},{"issue":"2","key":"10.1016\/j.knosys.2026.115626_bib0032","first-page":"1184","article-title":"Split then refine: stacked attention-guided ResUNets for blind single image visible watermark removal","volume":"35","author":"Cun","year":"2021","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.knosys.2026.115626_bib0033","article-title":"Pytorch: an imperative style, high-performance deep learning library","volume":"32","author":"Paszke","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.knosys.2026.115626_bib0034","unstructured":"D.P. Kingma, J. Ba, Adam: a method for stochastic optimization, arXiv preprint arXiv: 1412.6980(2014)."},{"key":"10.1016\/j.knosys.2026.115626_bib0035","series-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","first-page":"234","article-title":"U-Net: convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.knosys.2026.115626_bib0036","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Single image reflection separation with perceptual losses","author":"Zhang","year":"2018"},{"key":"10.1016\/j.knosys.2026.115626_bib0037","doi-asserted-by":"crossref","first-page":"4759","DOI":"10.1109\/TIP.2020.2975979","article-title":"Improving the harmony of the composite image by spatial-separated attention module","volume":"29","author":"Cun","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2026.115626_bib0038","doi-asserted-by":"crossref","unstructured":"X. Cun, C.-M. Pun, C. Shi, Towards ghost-free shadow removal via dual hierarchical aggregation network and shadow matting GAN, 2019. 1911.08718.","DOI":"10.1609\/aaai.v34i07.6695"},{"key":"10.1016\/j.knosys.2026.115626_bib0039","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Blind visual motif removal from a single image","author":"Hertz","year":"2019"},{"key":"10.1016\/j.knosys.2026.115626_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.107077","article-title":"DFCL: dual-pathway fusion contrastive learning for blind single-image visible watermark removal","volume":"184","author":"Meng","year":"2025","journal-title":"Neural Netw."}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126003667?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126003667?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T18:35:47Z","timestamp":1774031747000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705126003667"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":40,"alternative-id":["S0950705126003667"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2026.115626","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"GSGM : Gradient space guidance method for single-image visible watermark removal","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2026.115626","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115626"}}