计算机工程与应用2026，Vol.62Issue(8)：298-307,10.DOI:10.3778/j.issn.1002-8331.2503-0005
融合频域信息的双目图像超分辨重建Mamba网络
Frequency-Assisted Mamba Network for Stereo Image Super-Resolution
摘要
Abstract
Stereo image super-resolution(SSR)aims to exploit image information from two different perspectives of the binocular camera to generate images with higher resolution and richer details.Currently,Transformer-based SSR methods can capture global dependencies and obtain extensive contextual information through self-attention mechanisms.However,the computational complexity gets a quadratic increase with the sequence length,resulting in a low efficiency.Therefore,a new stereo image super-resolution network model based on Mamba architecture(MambaSSR)is proposed.The Mamba architecture has linear computational complexity,which can significantly improve the running efficiency of algorithms,and has the same powerful functions as Transformers.In addition,a frequency domain attention module is designed in the proposed MambaSSR model to preserve key frequency information.Thereby,more accurate texture details are recon-structed.Experiments are conducted on several public datasets,and the experimental results show that compared with mainstream methods,the proposed Mamba model can achieve excellent super-resolution reconstruction results with higher running efficiency.关键词
双目图像/图像超分辨重建/Mamba/频域Key words
stereo image/image super-resolution/Mamba/frequency domain分类
信息技术与安全科学引用本文复制引用
马鸣声,张德..融合频域信息的双目图像超分辨重建Mamba网络[J].计算机工程与应用,2026,62(8):298-307,10.基金项目
国家自然科学基金(62271035) （62271035）
北京市自然科学基金(4232021). （4232021）
