Edge detection based on joint iteration ghost imaging

Imaging and edge detection have been widely applied and played an important role in security checking and medical diagnosis. However, as we know, most edge detection based on ghost imaging system requires large measurement times and the target object image cannot be provided directly. In this work, a new edge detection based on joint iteration of projected Landweber iteration regularization and guided filter ghost imaging method has been proposed, which can improve the feature detection quality in ghost imaging. This method can also achieve high-quality imaging. Simulation and experiment results show that the spatial information and edge information of target object are successfully recovered from the random speckle patterns without special coding under a low measurement times, and the edge image quality is improved remarkably. This approach improves the the applicability of ghost imaging and can satisfy the practical application fields of imaging and edge detection at the same time. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement