Multidirectional edge detection based on gradient ghost imaging

Abstract

Gradient ghost imaging (GGI) is a new imaging method that can directly obtain the edge information of an unknown object from the correlation of light intensity fluctuations. However, this technique faces the problems of poor directionality and continuity. In this paper, we propose a multidirectional gradient ghost imaging scheme (MGGI), where Kirsch operator with 8-directional masks is first used to generate structured illuminations, and then a fast algorithm based on the connection of the 8 masks is applied in the sampling process. Compared with GGI based on Sobel operator, both simulation and experimental results demonstrate that the proposed method has the advantages of imaging quality and edge continuity even in a noisy environment. Furthermore, the MGGI does not increase the imaging time and thus promotes the practical development of ghost imaging.