Photometric Correction for Infrared Sensors
This addresses the challenge of enabling accurate 3D reconstruction from infrared sensors for applications like thermography, though it is incremental as it adapts existing SfM methods.
The paper tackled the problem of 3D reconstruction from infrared images by proposing a photometric correction model based on temperature constancy, and it demonstrated that the corrected imagery achieves performance on par with state-of-the-art RGB sensor reconstruction.
Infrared thermography has been widely used in several domains to capture and measure temperature distributions across surfaces and objects. This methodology can be further expanded to 3D applications if the spatial distribution of the temperature distribution is available. Structure from Motion (SfM) is a photometric range imaging technique that makes it possible to obtain 3D renderings from a cloud of 2D images. To explore the possibility of 3D reconstruction via SfM from infrared images, this article proposes a photometric correction model for infrared sensors based on temperature constancy. Photometric correction is accomplished by estimating the scene irradiance as the values from the solution to a differential equation for microbolometer pixel excitation with unknown coefficients and initial conditions. The model was integrated into an SfM framework and experimental evaluations demonstrate the contribution of the photometric correction for improving the estimates of both the camera motion and the scene structure. Further, experiments show that the reconstruction quality from the corrected infrared imagery achieves performance on par with state-of-the-art reconstruction using RGB sensors.