Efficient edge detection based on ghost imaging

Abstract

Edge detection has been widely applied in computer vision and pattern recognition. Ghost imaging (GI) based edge detection can directly obtain the edges without first requiring the object image. In this paper, we propose an efficient edge detection method based on GI, where a novel variable size Sobel operator (called the V-Sobel operator) whose coefficients are isotropic and sensitive to all directions is first designed, and then “calculated speckles” are computed by the V-Sobel operator to keep the number of measurements in the GI system unchanged with the size of V-Sobel operator. Both experimental and simulation results have demonstrated the feasibility of the proposed edge detection method. Furthermore, compared with the edges obtained by GI based edge detection by using the Sobel operator, the edges acquired by the proposed method are clearer and more continuous even under a severely noisy environment. In particular, when the detection SNR is as low as 11.89dB, the proposed method can also achieve a complete and clear edge, while the method using Sobel operator cannot.