Confidence-based camera calibration with modified census transform

Most camera calibration methods assume that the camera is nearly in-focus for precisely estimating the intrinsic and extrinsic camera parameters. However, the camera is generally out-of-focus in real calibration applications. This paper presents a method that is capable of accurately calibrating an out-of-focus camera. A confidence-based camera calibration with modified census transform (MCT) is proposed for a checkerboard calibration pattern. No additional devices or special calibration targets are required. First, the MCT utilizes the intensity information and local image structure to construct a descriptor. Then, the dissimilarity between the control point on the real image and the one on the sharp image is evaluated using the Hamming distance. This similarity metric is treated as the confidence of each control point. Finally, the confidence of each control point is added to the calibration energy minimization procedure to enhance the calibration performance. The experimental results on real images demonstrate that the proposed method achieves a more accurate calibration result than conventional methods.