摘要
全息影像在重建后经常会出现背景模糊等现象,为提高影像重建质量,设计融合注意力机制的模糊全息影像重建方法。设置像素点恢复与退化机制,对像素点采样与噪声进行模糊处理,关联区域内数值背景,建立全息影像像素捕捉模型,获取相同的特征序列维度,计算目标图像的背景信息,对不同空间采样频率的排列矩阵进行线性差值处理,采用融合注意力机制设计全息影像背景增强方法,采用模糊全息影像重建算法计算补偿函数,得到重建后全息影像。最后测试结果表明,所提方法可以得到最清晰的基础图案以及背景信息,结构相似性指数均在0.85以上,重建效果明显优于对比方法。
In order to improve the quality of image reconstruction,a fuzzy holographic image reconstruction method integrating attention mechanism is designed.It sets the pixel recovery and degradation mechanism,blurs the pixel sampling and noise,correlate the numerical background in the region,establishes the holographic image pixel capture model,obtains the same feature sequence dimension,calculates the background information of the target image,processes the linear difference of the array matrix of different spatial sampling frequencies,and designs the holographic image background enhancement method by using the fusion attention mechanism.The fuzzy holographic image reconstruction algorithm is used to calculate the compensation function,and the reconstructed holographic image is obtained.Finally,the test results show that this method can get the clearest basic pattern and background information.Structure similarity index is above 0.85,and the reconstruction effect is significantly better than the comparison method.
作者
李仕友
LI Shi-you(Haikou University of Economic,Haikou 570100 China)
出处
《自动化技术与应用》
2024年第9期122-125,共4页
Techniques of Automation and Applications
基金
2020年度海南省哲学社会科学规划课题(HNSK(YB)20-58)。
关键词
注意力机制
图像处理
全息影像技术
噪声模糊处理
像素捕捉模型
影像重建
attention mechanism
image processing
holographic image technology
noise fuzzy processing
pixel capture model
image reconstruction
