Depth Estimation Method for Monocular Camera Defocus Images in Microscopic Scenes

When using a monocular camera for detection or observation, one only obtain two-dimensional information, which is far from adequate surgical robot manipulation and workpiece detection. Therefore, at this scale, obtaining three-dimensional information of the observed object, especially depth estimation surface points each has become key issue. This paper proposes two methods to solve problem defiant images in microscopic scenes. These are method defocused image based on Markov random field, geometric constraints. According real aperture imaging principle, constraints relative defocus parameters point spread function derived, improves traditional iterative algorithm’s efficiency.