{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T10:28:02Z","timestamp":1766053682324,"version":"3.48.0"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100019904","name":"Vellore Institute of Technology, Chennai","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100019904","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3640164","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T18:38:20Z","timestamp":1764873500000},"page":"207928-207940","source":"Crossref","is-referenced-by-count":0,"title":["Learning-Based Uncertainty-Guided Adaptive Image Denoising: A Multi-Scale Patch Selection Framework"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-3052-1438","authenticated-orcid":false,"given":"A.","family":"Shalini","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9468-7672","authenticated-orcid":false,"given":"Christy Jackson","family":"Joshua","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.38"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/tip.2007.901238"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.1998.710815"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/tip.2017.2662206"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00325"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00181"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.00564"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2839891"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01716"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295309"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01208"},{"issue":"2","key":"ref12","first-page":"1","article-title":"Brief review of image denoising techniques","volume":"20","author":"Parmar","year":"2020","journal-title":"J. Biomed. Sci."},{"issue":"1","key":"ref13","first-page":"1","article-title":"Image denoising in deep learning: A comprehensive survey","volume":"2","author":"Singh","year":"2022","journal-title":"Eng. Technol. J."},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10305-2"},{"key":"ref15","article-title":"Deep learning for image denoising: A survey","author":"Yu","year":"2019","journal-title":"arXiv:1905.08801"},{"key":"ref16","article-title":"Self-supervised denoising for mixed Poisson\u2013Gaussian noise with SURE loss","author":"Aissa","year":"2024","journal-title":"arXiv:2401.09231"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02380"},{"issue":"4","key":"ref18","first-page":"29","article-title":"Comparing U-Net based models for denoising color images","volume":"1","author":"Calvarons","year":"2021","journal-title":"Imag. Syst. Technol."},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-89451-w"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-72912-z"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1002\/cav.70030"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW67362.2025.00125"},{"key":"ref23","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NeurIPS)","volume":"33","author":"Ho"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"ref25","first-page":"1","article-title":"Resfusion: Denoising diffusion probabilistic models for image restoration based on prior residual noise","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Shi"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-34341-2"},{"issue":"8","key":"ref27","article-title":"On denoising diffusion probabilistic models for synthetic aperture radar despeckling","volume":"17","author":"Perera","year":"2025","journal-title":"Remote Sens."},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2024.0358"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02111"},{"key":"ref30","first-page":"1","article-title":"SplitterNet: Efficient processing for mobile image denoising","volume-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit. Workshops (CVPRW)","author":"Flepp"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-60139-x"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-92283-3"},{"issue":"8","key":"ref33","first-page":"1523","article-title":"Overview of research on digital image denoising methods","volume":"14","author":"Wang","year":"2025","journal-title":"Electronics"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.14270"},{"key":"ref35","first-page":"29538","article-title":"Uncertainty-aware source-free adaptive image super-resolution with wavelet augmentation transformer","volume-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR)","author":"Yuan"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.13253"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-023-1466-0"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-025-07742-5"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/11278172.pdf?arnumber=11278172","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T10:23:47Z","timestamp":1766053427000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11278172\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3640164","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2025]]}}}