Efficient Focus Sampling Through Depth-of-Field Calibration

摘要

Due to the limited depth-of-field (DOF) of conventional digital cameras, only the objects within a certain distance range from the camera are in focus. Objects outside the DOF are observed with different amounts of defocus depending on their position. Focus sampling consists of capturing different images of the same scene by changing the focus configuration of the camera in order to alternately bring objects at different depths into focus. Focus sampling is an important part of different focus-related applications such as autofocus, focus stacking and depth estimation. This work proposes a calibration procedure for modeling the depth-of-field of conventional cameras in order to perform an efficient focus sampling. The method is simple in terms of repeatability and can be easily implemented in different imaging devices. Experimental tests are presented in order to illustrate the effectiveness of the proposed approach in autofocus. Results demonstrate that a significant reduction in the number of frames required to capture during autofocusing can be achieved by means of the proposed methodology.