基于特征交互融合与注意力的光场图像超分辨率  

Light Field Image Super-Resolution Based on Feature Interaction Fusion and Attention Mechanism

作　　者：徐欣宜 邓慧萍[1,2] 向森 吴谨 Xu Xinyi;Deng Huiping;Xiang Sen;Wu Jin(School of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,Hubei,China;Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education,Wuhan University of Science and Technology,Wuhan 430081,Hubei,China)

机构地区：[1]武汉科技大学信息科学与工程学院,湖北武汉430081 [2]武汉科技大学冶金自动化与检测技术教育部工程研究中心,湖北武汉430081

出　　处：《激光与光电子学进展》2023年第14期160-169,共10页Laser & Optoelectronics Progress

摘　　要：光场图像包含丰富的空间信息和角度信息,在三维重建、虚拟现实领域有广泛应用。但由于光场相机的内部限制,光场图像的低空间分辨率阻碍了其应用发展,具体表现为图像边缘区域的模糊。考虑到光场子孔径图像中空间信息包含着丰富的纹理和高频细节,而角度信息则对应不同视图之间的相关性,提出一种基于特征交互融合与注意力的光场图像超分辨率网络。通过特征提取和特征交互融合模块充分融合光场的空间角度信息;通过特征通道注意力模块自适应地学习有效信息,抑制冗余信息并细化图像的高频细节;通过光场结构一致性模块保持光场图像间的视差结构。在5个光场数据集上的实验结果表明,所提网络得到的超分辨率结果性能普遍优于所比较的超分辨率网络。Light field images contain rich spatial and angle information and are,therefore,widely used in threedimensional reconstruction and virtual reality;however,the limited spatial resolution of light field pictures,notably the blurring of the image edge area,prevents their application and development due to the inherent constraints of light field cameras.A light field image super-resolution network based on feature interactive fusion and attention is proposed here because the spatial information in a light field subaperture image contains rich texture and high-frequency details and the angle information corresponds to the correlation between different views.Here,the feature extraction and feature interactive fusion modules completely fuse the spatial and angle information of the light field;the feature channel attention module refines high-frequency aspects of the images by adaptively learning effective information and suppressing redundant information;and the optical field structure consistency module preserves the parallax structure between optical field pictures.The performance of the proposed network is typically superior to that of the compared super-resolution network,according to the experimental results from five light field datasets.

关 键 词：图像处理 超分辨率 深度学习 光场图像 注意力机制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]