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.

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.