Improvement of photogrammetric accuracy by modeling and correcting the thermal effect on camera calibration

Abstract

This paper presents a new method for improving the geometric accuracy of photogrammetric reconstruction by modeling and correcting the thermal effect on camera image sensor. The objective is to verify that when the temperature of image sensor varies during the acquisition, image deformation induced by the temperature change is quantifiable, modelisable and correctable. A temperature sensor integrated in the camera enables the measurement of image sensor temperature at exposure. It is therefore natural and appropriate to take this effect into account and to finally model and correct it after a calibration step. Nowadays, in cartography applications performed with UAV, the frame rate of acquisitions is continuously increasing. A high frame rate over a long acquisition time can result in an important temperature increase of the image sensor and thus introduces image deformations. The correction of the above-mentioned effect can improve the measurement accuracy. We present three methods to calibrate the thermal effect and experiments on two datasets are carried out to verify the improvement in terms of the photogrammetric accuracy.

Simulation and Analysis of Photogrammetric UAV Image Blocks—Influence of Camera Calibration Error

“…The focal length of the last image (5513.48 pixels) is 3.10 pixels greater then that of the first image (5510.38 pixels). According to the relation between the focal length and the camera internal temperature given by Reference [31], an increase of 3.10 pixels corresponds to a temperature increase of around 40 • C for a focal length of 35 mm as in our experiments. The amplitude of the temperature variation is realistic and conforms to real acquisition conditions.…”

“…It is not certain that the focal length increases linearly in real life. Actually, as shown in Reference [31], the increment speed of the temperature decreases with time and the focal length increases linearly with the temperature. Here, the linear model is chosen to model the focal length variation for its simplicity of interpretation.…”

“…Merchant investigated the variation of the focal length induced by the temperature change for a Nikon lens of 20 mm, a variation of 0.5 µm per degree is observed [29,30]. Daakir and Zhou calibrated and corrected the image deformation caused by the variation of camera internal temperature, the 3D reconstruction accuracy was improved by 1.4 times for an aerial dataset of corridor configuration [31].…”

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

“…Thus, the thermal image can be unreliable especially when the internal temperature of the camera is changing rapidly, such as during camera warmup period or during the flight when a gust of cool wind results in cooling of the camera. To overcome this challenge, the user may need to provide sufficient startup time before operation (preferably 30-60 min) [102,[143][144][145], shield the camera to minimize the change in the internal temperature of the camera [142], calibrate the camera [146][147][148][149][150][151][152][153], and perform frequent flat-field corrections.…”

The Test Field for Uav Accuracy Assessments

“…The research has showed out that in some cameras the focal length and principal point position are changing in several dozen of microns, although between calibration the camera was not operationally used. It is worth underlining that also thermal conditions impact the parameters of interior orientation (Daakir, 2019).…”