图像融合
人工智能
像素
计算机视觉
融合
计算机科学
灰度
共焦
光学(聚焦)
图像处理
光学
图像(数学)
物理
哲学
语言学
作者
Tao Yuan,Wei Jiang,Yiqing Ye,Dongliang wu,Yongjie Hai,Dingrong Yi
出处
期刊:Applied Optics
[The Optical Society]
日期:2023-07-03
卷期号:62 (21): 5772-5772
摘要
Aiming at the problems of poor anti-interference of existing pixel-level fusion rules and low efficiency of transform domain fusion rules, this study proposes a confocal microscopic multi-focus image fusion method (IGCM) based on differential confocal axial information guidance. Unlike traditional multi-focus image fusion (MFIF) methods, IGCM uses height information rather than grayscale or frequency to determine clear areas. First, the differential confocal axial measurement curve is calibrated to determine the suitable scan step u. Second, the image set required for fusion is constructed by performing a hierarchical scan of the measurement samples. Then, multiple differential image pairs are constructed using the step size u and the set of images, and the extraction area of the current reference image is decided based on the height obtained from the differential image. Finally, the regions determined by each reference image are extracted and the duplicated pixels are averaged to obtain the MFIF image. The results were that IGCM improves the interference immunity based on pixel-level image fusion compared to the maximum peak fusion method. Compared with other MFIFs, IGCM has excellent fusion efficiency while ensuring fusion clarity, which can meet the application scenario of real-time fusion and offers a new approach to panoramic depth images for confocal devices.
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