索贝尔算子
光学
斑点检测
微分边缘检测器
卷积(计算机科学)
傅里叶变换
像素
人工智能
计算机视觉
GSM演进的增强数据速率
操作员(生物学)
图像处理
边缘增强
高斯分布
Canny边缘检测器
边缘检测
计算机科学
数学
物理
图像(数学)
人工神经网络
基因
转录因子
数学分析
量子力学
抑制因子
生物化学
化学
作者
Liyu Zhou,Xianwei Huang,Qin Fu,Xuanpengfan Zou,Yanfeng Bai,Xiquan Fu
标识
DOI:10.3788/col202119.121101
摘要
Typical single-pixel imaging techniques for edge detection are mostly based on first-order differential edge detection operators. In this paper, we present a novel edge detection scheme combining Fourier single-pixel imaging with a second-order Laplacian of Gaussian (LoG) operator. This method utilizes the convolution results of an LoG operator and Fourier basis patterns as the modulated patterns to extract the edge detail of an unknown object without imaging it. The simulation and experimental results demonstrate that our scheme can ensure finer edge detail, especially under a noisy environment, and save half the processing time when compared with a traditional first-order Sobel operator.
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