高效的基于傅里叶单像素成像的亚像素级边缘检测技术

Efficient Sub-Pixel Edge Detection Technique Based on Fourier Single-Pixel Imaging

针对无法实现先验的边缘检测场景,并解决边缘提取效率过低的问题,提出一种更高效的基于傅里叶单像素成像的亚像素级边缘检测方法。该方法结合快速傅里叶单像素成像,减少图像算法的相移步数,在原有四步相移的基础上分别实现了三步相移与两步相移边缘检测。该算法上的改进能够在同等采样数下扩大参与边缘提取的频谱宽度,从而提升边缘提取效率。数值仿真结果表明,与四步相移亚像素级边缘检测相比,无噪声条件下两步相移在655~13 100次左右的采样数区间内峰值信噪比增长幅度高出2.27 dB,噪声条件下低于0.054噪声浮动比率时两步相移方法可以获得比四步相移更高的边缘提取质量。该方法可以一定程度上提升边缘提取效率,同时促进单像素成像领域与图像处理方向的技术交叉和应用化发展。

In order to solve the problem that the edge detection cannot be realized a prior and the edge extraction efficiency is too low,a more efficient subpixel level edge detection method based on Fourier single pixel imaging is proposed.Combined with fast Fourier single pixel imaging,this method reduces the number of phase shift steps of the image algorithm,and realizes the three-step phase shift and two-step phase shift edge detection respectively on the basis of the original four-step phase shift.The improvement of the algorithm can expand the spectrum width of edge extraction under the same number of samples,so as to improve the efficiency of edge extraction.The numerical simulation results show that,compared with the four-step phase shift subpixel level edge detection,the peak signal-to-noise ratio(PSNR)increases 2.27 dB in the sampling range of 655~13100 times under the condition of no noise,and the two-step phase shift method can obtain a higher edge extraction quality than the four-step phase shift when the noise floating ratio is lower than 0.054.The method proposed in this paper can improve the efficiency of edge extraction to a certain extent,and promote the technology crossover and application development of the single pixel imaging field and image processing direction.