The array spatial light field is an effective means for improving imaging speed in single-pixel imaging. However, distinguishing the intensity values of each sub-light field in the array spatial light field requires the help of the array detector or the time-consuming deep-learning algorithm. Aiming at this problem, we propose measurable speckle gradation Hadamard single-pixel imaging (MSG-HSI), which makes most of the refresh mechanism of the device generate the Hadamard speckle patterns and the high sampling rate of the bucket detector and is capable of measuring the light intensity fluctuation of the array spatial light field only by a simple bucket detector. The numerical and experimental results indicate that data acquisition in MSG-HSI is 4 times faster than in traditional Hadamard single-pixel imaging. Moreover, imaging quality in MSG-HSI can be further improved by image stitching technology. Our approach may open a new perspective for single-pixel imaging to improve imaging speed.

关联成像是通过对测得的参考光和信号光进行关联计算来获取物体信息的新型成像技术。在复杂环境中，湍流、散射等因素会以噪声的形式影响信号光的测量。由于关联成像中信号光是以桶探测器来测量的，因此，对这种含噪信号光的处理及其在关联成像过程中的影响有必要进行系统地研究。文中系统地回顾了笔者所在课题组在上述背景下的相关研究。首先，简述了复杂环境下的关联成像模型；然后，分析了含噪信号光对二值目标和灰度目标关联成像的影响；接着，对大气信道中湍流引起的信号噪声进行了测量和分析，最后，对关联成像的应用进行了展望。

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.