Geometric calibration of a hyperspectral frame camera with simultaneous determination of sensors misalignment

Abstract

The recent development of lightweight and relatively low-cost hyperspectral sensors has created new perspectives for remote sensing applications. This study aimed to investigate the geometric calibration of a hyperspectral frame camera based on a tuneable Fabry–Pérot interferometer (FPI) and two sensors. The radiation passes through the optics and then through the FPI, where it is redirected to two sensors using a beam-splitting prism. Previous studies have shown significant variations between the interior orientation parameters for the different bands, both between bands of the same sensor and between different sensors, and that these variations are due to the principle of image acquisition. Discrepancies of tens of pixels were obtained by comparing image coordinates measured in different bands. In this research, it was proposed to calibrate this camera in a static mode with changes in the mathematical calibration model. The restriction of obtaining only one set of exterior orientation parameters by hypercube was applied, adding parameters related to the misalignment between the sensors and parameters of a linear function relating the camera principal distance to the wavelength values. The application of the parameters estimated with this approach reduced the discrepancies between image coordinates measured in different bands to values smaller than one pixel. Using the sensor calibration parameters in the mobile UAV operation in an aerial bundle adjustment reduced the root mean square error (RMSE) on checkpoints by approximately 20% compared to the traditional model in which the interior orientation parameters and lens distortions were calibrated for each band separately. Thus, it was possible to obtain accurate results that make the use of this camera more practical since only one set of calibration parameters for all bands is needed.