Principles of self-calibration and visual effects for digital camera distortion

Abstract

Producing accurate spatial data with stereo photogrammetric techniques is a challenging task, and the central projection of the space needs to be defined as closely as possible to its real form in each image taken for the relevant production. Interior camera parameters that define the exact imaging geometry of the camera and the exterior orientation parameters that locate and rotate the imaging directions in a coordinate system have to be known accurately for this correct definition. All distortions sourcing from lens and sensor planes and their recording geometry are significant as they are not suitable for detection with manual measurements. It is of vital importance to clearly understand the camera self-calibration concept with respect to the lens and the sensor plane geometry and include every possible distortion source as an unknown parameter in the calibration adjustments as they are all modellable systematic errors. In this study, possible distortion sources and self-calibration adjustments are explained in detail with a recently developed visualization software. The distortion sources investigated in the study are radial, tangential, differential scale, and axial skewing distortion. Thanks to the developed software, image center point, distorted grids, undistorted grids, and principal points were visualized. As a result, the most important element of obtaining accurate and precise photogrammetric productions is the correct definition of the central projection of the space for each image, and therefore, the study explains an accurate and robust procedure with the correct definition and use of correct camera internal parameters.

Keywords

• camera calibration
• sensor calibration
• least-squares adjustment
• lens distortion
• sensor plane distortion