The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLII-4/W18
18 Oct 2019
 | 18 Oct 2019


S. A. Fakhri and S. A. Fakhri

Keywords: PSO, Calibration, non-metric camera, close range, control point, collinearity equation

Abstract. Over the past decades, non-metric cameras have been utilized in functions with less accuracy requirement or even in precise works with the progress of photogrammetric cameras developed technology. One of the reasons to use these kinds of cameras is due very much to their lower costs in comparison with the metric ones. Since we have always error in measurements, there is no exception in Photogrammetry, which is more in the non-metric cameras than the metric ones. Some of these errors are systematic and the only way to cope with them is to model. So far, many models have been proposed to investigate and modify the behavior of errors. Some of these models are linear and some others are non-linear. The number of parameters in each model is different based on the complexity of error in each image. Since the picture need to be connected to earth to calculate the calibration parameters of the camera, therefore this connection is generally made through points known as the ground control points, and more of these control points are needed in the complex models with more sophisticated calculations. Using a method to reduce the need for less control points and achieving a suitable accuracy is beneficial due to the high cost and time-consuming process of preparing the control points. One of the methods that could be used in solving the calibration equations is the Particle Swarm Optimization (PSO) algorithm. Images of a few targets are captured in this research by a non-metric camera and the collinearity equations are used by adding further correction terms in order to calibrate the camera. The results of PSO method are compared with the classical mathematical methods in each step by reducing the number of control points, which indicated that the performance of using the PSO algorithm is better than the conventional proration methods in reducing the number of points and could be utilized in projects suffering from the lack of control points.