Image super-resolution reconstruction based on feature map attention mechanism

• Published in: Applied intelligence (Dordrecht, Netherlands) Vol. 51; no. 7; pp. 4367 - 4380
• Main Authors: Chen, Yuantao, Liu, Linwu, Phonevilay, Volachith, Gu, Ke, Xia, Runlong, Xie, Jingbo, Zhang, Qian, Yang, Kai
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.07.2021; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Computer Science; Deep learning; Feature extraction; Feature maps; Image reconstruction; Image resolution; Image restoration; Information retrieval; Machines; Manufacturing; Mapping; Mechanical Engineering; Modules; Processes; Signal to noise ratio; Similarity; Visual effects; Feature map attention mechanism; Multi-scale low-resolution images; Multiple information extraction; Image super-resolution reconstruction; Deep learning methods

To improve the issue of low-frequency and high-frequency components from feature maps being treated equally in existing image super-resolution reconstruction methods, the paper proposed an image super-resolution reconstruction method using attention mechanism with feature map to facilitate reconstru...