Camera Calibration and Performance Evaluation of Depth From Defocus (DFD)

Real-time and accurate autofocusing of stationary and moving objects is an important problem in modern digital cameras. Depth From Defocus (DFD) is a technique for autofocusing that needs only two or three images recorded with different camera parameters. In practice, there exist many factors that affect the performance of DFD algorithms, such as nonlinear sensor response, lens vignetting, and magnification variation. In this paper, we present calibration methods and algorithms for these three factors. Their correctness and effects on the performance of DFD have been investigated with experiments.