Dual-parameter linear imaging model based automatic high dynamic range 3D measurement and multi-weight phase fusion method

Although Fringe Projection Profilometry (FPP) has emerged as an efficient 3D measurement technique, achieving automatic High Dynamic Range (HDR) measurements remains challenging. Traditional automatic HDR methods are limited by the nonlinear relationship between projector radiance and current, solely relying on exposure time adjustment, which restricts the achievable dynamic range. Moreover, the traditional approach of selecting the brightest unsaturated phase has proven insufficient for improving measurement accuracy. This paper presents a dual-parameter linear imaging model to address these limitations. The proposed model introduces a reference current and implements a current ratio factor, enabling linear control of both exposure time and projector radiance. This approach overcomes the limitations of single-parameter exposure adjustments and nonlinear radiation response, thereby substantially expanding the dynamic range of the FPP system. We propose an automatic method for computing optimal exposure sequences that eliminates the need for surface reflectance calculations, thus enhancing computational efficiency. Furthermore, we develop a multi-weight phase fusion method to improve measurement accuracy. Experimental results demonstrate the effectiveness of our proposed method in automatic HDR object measurement.