突出
衍射
特征(语言学)
计算机科学
特征提取
模式识别(心理学)
人工智能
样品(材料)
噪音(视频)
图像质量
方向(向量空间)
计算机视觉
图像(数学)
算法
光学
数学
物理
热力学
几何学
哲学
语言学
作者
Xuyang Zhou,Ziyang Li,Ziling Qiao,Yiran Wang,Guancheng Huang,Dazhao Chi,Xiaomei Li,Shutian Liu,Zhengjun Liu
标识
DOI:10.1002/jbio.202300278
摘要
Abstract In multi‐distance coherent diffraction imaging, the task of distance calculation for multi‐diffraction images is cumbersome. The information features are hard‐to‐extract and the region of interest extraction algorithms are difficult to be adopted. A universal salient feature region selection algorithm by using the area with the highest density of corners is proposed to extract the most representative feature region. In addition, equally spaced recording modes and mismatched diffraction distances will result in system noise and destroy image quality. The polydirectional maximum gradient is offered as a sharpness criterion to weigh a quantitative feature for the final pattern. A fast, sensitive, and high‐accuracy autofocusing and sample reconstruction can be achieved using only a small number of images while ensuring that morphological properties and quantification of the reconstructions are not compromised. The proposed method is promising for biological and medical dynamic observations for computational imaging systems.
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