首页> Scientific reports> Hierarchical sparse Bayesian learning with adaptive Laplacian prior for single image super-resolution.

Hierarchical sparse Bayesian learning with adaptive Laplacian prior for single image super-resolution.

导出 LinkOut

翻译打印收藏纠错

第一作者： Mingming,Qi

第一单位： School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou, 325000, China.;Key Laboratory of Data Intelligence and Governance of Wenzhou City, Wenzhou, 325000, China.

作者： Mingming,Qi ^[1] ; Yue,Zhou ^[2] ; Yiwei,Hu ^[3] ; Cuihua,Xie ^[4] ; Shuhua,Xu ^[5]

作者单位： School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou, 325000, China.;Key Laboratory of Data Intelligence and Governance of Wenzhou City, Wenzhou, 325000, China. ^[1] Wenzhou Federation of Trade Unions Workers' Technical Cooperation Center, Wenzhou, 325000, China. ^[2] College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325000, China. ^[3] School of Economics and Management, Wenzhou University of Technology, Wenzhou, 325000, China. ^[4] School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou, 325000, China. 247141328@qq.com.;Key Laboratory of Data Intelligence and Governance of Wenzhou City, Wenzhou, 325000, China. 247141328@qq.com. ^[5]

关键词 Adaptive laplacian prior Hierarchical bayesian model Pixel variance estimation Single image super-resolution (SISR)Sparse bayesian learning (SBL)Spatial alternating optimization

DOI 10.1038/s41598-025-20115-5

PMID 41107281

发布时间 2025-10-20

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交