Since it is difficult to denoise and simplify a three dimensional point cloud data by a same parameter, a new unified algorithm based on the Extended Surface Variation based Local Outlier Factor (ESVLOF) for denoising and simplification of scattered point cloud was proposed. Through the analysis of the definition of ESVLOF, its properties were given. With the help of the surface variability computed in denoising process and the default similarity coefficient, the parameter γ which decreased with the increase of surface variation was constructed. Then the parameter γ was used as local threshold for denoising and simplifying point cloud. The simulation results show that this method can preserve the geometric characteristics of the original data. Compared with traditional 3D point-cloud preprocessing, the efficiency of this method is nearly doubled.