Fast Position Bit Depth Estimation for Near‐Lossless Gaussian Splatting Representation

ABSTRACT 3D Gaussian splatting enables real‐time, photorealistic novel view synthesis using millions of 3D Gaussian primitives, but its adoption is hindered by high storage demands. This letter presents a fast statistical method to estimate the optimal position bit‐depth for near‐lossless compression, without rendering or PSNR computation. By modelling duplicated point ratios in training data and applying outlier detection to test data, our method predicts the minimal acceptable bit‐depth. Experiments on multiple datasets show that the method takes approximately 1.24 s on average. This performance is achieved while preserving near‐lossless quality, making the approach practical for real‐time and resource‐constrained applications.