基于焦点像素的纤维成分检测多焦面融合成像  

Multi-focal plane fusion imaging of fiber component detection based on focal pixels

作　　者：杨宁[1,2] 杨志军 王沛森[1] 周全 孙晗 YANG Ning;YANG Zhijun;WANG Peisen;ZHOU Quan;SUN Han(State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment,Guangdong University of Technology,Guangzhou,Guangdong 510006,China;Hua Dao Super Precision Technology Company Limited,Foshan,Guangdong 528225,China)

机构地区：[1]广东工业大学精密电子制造技术与装备国家重点实验室,广东广州510006 [2]华道超精科技有限公司,广东佛山528225

出　　处：《纺织学报》2024年第12期50-57,共8页Journal of Textile Research

基　　金：国家重点研发计划项目(2022YFB4701001);教育部产学研教改项目(220904084262251)。

摘　　要：针对纤维成分显微检测中,单幅成像时视野中重叠纤维失焦模糊的问题,建立基于焦点像素的纤维多焦面融合算法。通过显微检测平台采集Z轴不同聚焦平面处的重叠纤维序列图像,并确定2幅局部最清晰源图像,之后对源图像使用多尺度修正拉普拉斯算子计算得到焦点像素,生成初始决策图;通过切片计算生成中间决策图;使用引导滤波器得到最终决策图,再采用近邻距离滤波器分解源图像得到高通和低通图像,最终加权得到融合图像;最后与多模态融合算法、3层分解稀疏融合去噪算法和非下采样连续变换算法进行主客观评估标准相比。结果表明:该融合算法得到的全局纤维边缘信息保留度更好,图像互信息较高且峰值信噪比大。该融合算法处理后的纤维图像达到全局纹理清晰聚焦的效果,能够有效改善局部纤维模糊问题。Objective Currently,textile testing technology requires high-quality fiber images as a fundamental condition to observe the fineness and maturity of textiles.However,obtaining high quality fiber images is challenging due to the out-of-focus blurring of overlapping fibers in the visual field during single image imaging.Therefore,achieving the effect of global texture sharpness focusing by multi-focal plane fusion,based on obtaining only the locally clearest source image of overlapping fibers,holds great theoretical significance and application value.Method To address the problem of defocus blur of overlapping fibers in the visual field during single image imaging,this research proposed a multi-focal plane fusion algorithm based for fibers on focal pixels.Firstly,two locally clearest source images were determined from the overlapping fiber images.Focal pixels were then obtained by multi-scale modified Laplacian algorithm to generate the initial decision map.The intermediate decision map was generated by slice calculation,and the guide filter was used to get the final decision map.Subsequently,the source image was processed with high-pass and low-pass respectively by the nearest neighbor distance filter.Finally,the fusion image was weighted.Results The fiber multi-focal plane fusion algorithm based on focal pixels was proved suitable for different fiber samples.In the experiment,four types of fiber samples were listed,named as sample 1(wool),sample 2(down hair),sample 3(cotton)and sample 4(rabbit hair).By comparing the locally out-of-focus fuzzy original images of different samples with the fused images,it was seen that the texture details and edge structures of different samples were very clear after processing by the proposed multi-focal plane algorithm.Overlapping wool fiber samples in the same region were selected to compare the differences among the multi-focal plane fusion algorithm based on focus pixels and multi-mode fusion algorithm,three-layer decomposition sparse fusion denoising algorithm and non-down sa

关 键 词：近邻距离滤波器 决策图学习 多焦面融合算法 纤维图像 纤维成分显微检测 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]