现代信息科技2024，Vol.8Issue(12)：27-31,5.DOI:10.19850/j.cnki.2096-4706.2024.12.007
一种改进的字典学习的教室图像超分辨率重建方法
An Improved Dictionary Learning Super-resolution Reconstruction Method for Classroom Images
摘要
Abstract
At present,the imaging of classrooms is affected by low equipment performance and complex environments,resulting in incomplete understanding of teachers and students in the teaching environment.In order to fully utilize image information and comprehensively and meticulously understand the teaching situation,this paper proposes an improved dictionary learning super-resolution reconstruction method for classroom image.By using dictionary learning algorithms to train a self constructed classroom image dataset,corresponding low rank and sparse dictionaries are obtained.The two trained dictionaries are used to reconstruct the training set images,and then participate in training to obtain residual dictionaries.Then,the three trained dictionaries are used to reconstruct low resolution images,ultimately high-resolution images are obtained.Comparative experiments are conducted between the proposed algorithm and several classic algorithms,and both visual and quantitative results show that the proposed algorithm achieved significant improvements in both PSNR and SSIM.关键词
低秩矩阵分解/局部线性嵌入/残差字典/图像超分辨率Key words
low rank matrix factorization/locally linear embedding/residual dictionary/image super-resolution分类
信息技术与安全科学引用本文复制引用
丁玉祥..一种改进的字典学习的教室图像超分辨率重建方法[J].现代信息科技,2024,8(12):27-31,5.基金项目
安徽省高校自然科学研究重点项目(2022AH052740) （2022AH052740）
