Image Super‐Resolution Reconstruction Based on the Lightweight Hybrid Attention Network
Chu Yuezhong,
Wang Kang,
Zhang Xuefeng
et al.
Abstract:In order to solve the problem that the current image super‐resolution model has too many parameters and high computational complexity, this paper proposes a lightweight hybrid attention network (LHAN). LHAN consists of three parts: shallow feature extraction, lightweight hybrid attention block (LHAB), and upsampling module. LHAB combines multiscale self‐attention and large‐core attention. In order to make the network lightweight, multiscale self‐attention block (MSSAB) improves the self‐attention mechanism and… Show more
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