湖南大学学报（自然科学版）2023，Vol.50Issue(12)：10-18,9.DOI:10.16339/j.cnki.hdxbzkb.2023294
细粒度全局感知多聚焦图像融合网络
Fine-grained Global Perception Multi-focus Image Fusion Network
摘要
Abstract
Multi-focus image fusion is an prominent branch of image fusion,which is widely used in microscopic imaging.Aiming at the problems of unclear texture details and misjudgment of focus areas in multi-focus fusion,this paper designs a global information encoding-decoding network from the perspective of global attention of spatial and channel information,combined with the shifted window self-attention mechanism in Swin Transformer and deep separable convolution.The comprehensive loss function is used to perform unsupervised learning of image reconstruction tasks.From the perspective of the importance of feature neighborhood information,an improved Laplacian energy sum function is introduced to discriminate the image focusing-properties in the feature domain,and the fine-grained effect of image focusing region discrimination is enhanced.Compared with seven classical image fusion algorithms,the proposed algorithm achieves advanced fusion performance in both qualitative and quantitative analysis and has a higher fidelity effect on the focus area information of the original image.关键词
多聚焦图像融合/自注意力机制/改进的拉普拉斯/无监督学习Key words
multi-focus image fusion/self-attention mechanism/improved Laplace/unsupervised learning分类
信息技术与安全科学引用本文复制引用
邬开俊,梅源..细粒度全局感知多聚焦图像融合网络[J].湖南大学学报（自然科学版）,2023,50(12):10-18,9.基金项目
甘肃省自然科学基金资助项目(23JRRA913),Natural Science Foundation of Gansu Province(23JRRA913) （23JRRA913）
内蒙古重点研发和成果转化项目(2023YFSH0043),Inner Mongolia Key R & D and Achievement Transformation Project(2023YFSH0043) （2023YFSH0043）
甘肃省重点人才项目和甘肃省优秀研究生"创新之星"项目(2023CXZX-544),Key Talent Project of Gansu Province and Gansu Province Excellent Postgraduate"Innovation Star"Proiect(2023CXZX-544) （2023CXZX-544）
