A High-Efficient Algorithm for Sample-Based Synthesis of Vegetation Distribution

For the simulation of diverse distribution patterns of vegetation in natural scenes,the existing general distribution fitting algorithm was too time-consuming to meet the needs of large-scale distribution or real-time interactive distribution synthesis.In order to achieve rapid synthesis of arbitrary distribution patterns,an efficient point distribution synthesis method based on sample patterns control combined with Wang tiles acceleration is proposed.The method consists of two key phases:an off-line pre-computing phase and a real-time tiling phase.In the pre-computing phase,the PCF feature fitting process based on toroidal point pair distance statistics is used to synthesize initial point distribution tiles with similar distribution patterns to samples and end to end feature continuity.Then a set of Wang tiles that can be tiled non-periodically and seamlessly is obtained by adjusting the boundaries of the initial tile.With these Wang tiles,the real-time tiling phase can synthesize large-scale distribution at extremely fast speed and with very small memory footprint.This method is a general distribution synthesis method applicable to data with various distribution patterns(random,uniform,and clumped),and achieves a speed improvement of 3-6 orders of magnitude over the original sample-based algorithm in the large-scale distribution synthesis.This method can be effectively applied to the construction of large-scale vegetation scenes and other applications with real-time interactive distribution.