RESUMO
A high dynamic range surface has large reflectivity variations and measuring it with a structured light technique could cause pixel saturation that will seriously degrade the measurement accuracy. Accurate identification of saturated pixels will significantly improve the measurement accuracy. This paper introduces an accurate estimation approach to the camera response function (CRF) for high dynamic range measurement and proposes a method that uses the estimated CRF to identify the saturated pixels in captured images. We perform experiments using the proposed saturation identification method and the other existing methods to compare both the saturation identification accuracy and measurement accuracy. The experiment results verify both the accuracy and suitability of the proposed method.
RESUMO
Among 3D measurement approaches, multi-frequency phase-shifting structured light has advantages such as high resolution and high sampling rate owing to its point-to-point calculation method. However, there is always phase jump in the measurement process, which greatly reduces measurement accuracy. This paper proposes an error self-correction method for phase jump based on the multi-frequency heterodyne approach. The method uses redundant measurement data to implement self-correction and does not require additional data acquisition steps. We perform both simulations and experiments using the proposed error self-correction method and the classical heterodyne approach to compare the results. The experiment results verify both the accuracy and suitability of the proposed method.