计算机工程2024，Vol.50Issue(7)：314-323,10.DOI:10.19678/j.issn.1000-3428.0067857
基于局部分离与多尺度融合的图像超分辨率重建
Image Super-Resolution Reconstruction Based on Partial Separation and Multiscale Fusion
摘要
Abstract
Currently,deep-learning-based super-resolution reconstruction networks suffer from issues such as convolution operation redundancy,incomplete image reconstruction information,and large model parameters that limit their applicability to edge devices.To address these issues,this study proposes a lightweight image super-resolution reconstruction network based on partial separation and multiscale fusion.This network utilizes partial convolutions for feature extraction and separates partial image channels to reduce redundant computations while maintaining the quality of the image reconstruction.At the same time,a multiscale feature fusion module is designed to learn long-range dependency features and capture spatial features in the spatial dimension using a channel attention enhancement group.This reduces the loss of image reconstruction information and effectively restores the details and textures of the image.Finally,because the multiscale feature fusion block focuses on global feature extraction and fusion,an efficient inverted residual block is constructed to supplement the ability to extract local contextual information.The network is tested on five benchmark datasets:Set 5,Set 14,B 100,Urban 100,and Manga 109,with scale factors of 2,3,and 4 times.The parameters of the network are 373 000,382 0000,and 394 000,and the FLOPs are 84.0×109,38.1×109,and 22.1×109,respectively.Quantitative and qualitative experimental results show that compared with networks such as VDSR,IMDN,RFDN,and RLFN,the proposed network ensures image reconstruction quality with fewer network parameters.关键词
超分辨率重建/轻量级网络/局部卷积/多尺度融合/长依赖关系Key words
super-resolution reconstruction/lightweight network/partial convolution/multiscale fusion/long-range dependencies分类
计算机与自动化引用本文复制引用
杨郅树,梁佳楠,曹永军,钟震宇,何永伦..基于局部分离与多尺度融合的图像超分辨率重建[J].计算机工程,2024,50(7):314-323,10.基金项目
佛山市重点领域科技攻关项目(2020001006827) （2020001006827）
广州市科技计划项目(202206010052). （202206010052）
