期刊论文

Chen, Yuantao

英文

Applied Intelligence

0924-669X

2021

51

7

4367-4380

10.1007/s10489-020-02116-1

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61972056, 61772454, 61402053, 61981340416]; Natural Science Foundation of Hunan Province of ChinaNatural Science Foundation of Hunan Province [2020JJ4623]; Scientific Research Fund of Hunan Provincial Education DepartmentHunan Provincial Education Department [17A007, 19C0028, 19B005]; Junior Faculty Development Program Project of Changsha University of Science and Technology [2019QJCZ011]; "Double First-class" International Cooperation and Development Scientific Research Project of Changsha University of Science and Technology [2019IC34]; Practical Innovation and Entrepreneurship Ability Improvement Plan for Professional Degree Postgraduate of Changsha University of Science and Technology [SJCX202072]; Postgraduate Training Innovation Base Construction Project of Hunan Province [2019-248-51, 2020-172-48]

本校为第一且通讯机构

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 reconstruction from original low-resolution images to multi-scale super-resolution images. The proposed model consists of a feature extraction block, an information extraction block, and a reconstruction module. Firstly, the extraction block is used to extract useful features from low-resolution images, with...