Aiming at the problems of modeling parameters limitation, low efficiency, high labor cost and lack of detail in existing modeling methods, this study proposes a bridge realistic reconstruction algorithm based on an improved 3D Gaussian splatting—FIPT-GS. First, this algorithm constrains the size of Gaussian kernels through a 3D filter to adapt to the complex geometric structure of bridges and reduce artifacts in outdoor scene modeling. Second, it introduces Gaussian approximation of the integral calculation window area to optimize lighting processing and enhance visual realism. Then, it also uses pixel gradient scaling to change the conditions of adaptive density control, so as to deal with the variation of depth of field and amplify the contribution of each pixel. Finally, it optimizes the input value by tensor decomposition to reduce computational difficulty and improve rendering efficiency. The experimental results show that the model quality is significantly improved with only a slight increase in rendering time. The peak signal-to-noise ratio improves by 7.0%, the structural similarity increases by 2.9%, and the learned perceptual image patch similarity decreases by 16.4%. The improved model, which maintains rendering speed, exhibits stronger anti-aliasing capability, provides richer details, and achieves higher image fidelity.