A New Algorithm for Solid Texture Synthesis

Abstract

Despite the tremendous rendering power offered by modern GPUs, real-time and photo-realistic rendering is still often out of reach of traditional polygonal-based rendering. Thanks to the invention of texture mapping, a scene with a moderate number of triangles could be readily and vividly rendered by nowadays popular and inexpensive graphics cards. However, as a desired texture often comes with a very limited size, the technique of texture synthesis, i.e., synthesizing a larger texture from an originally smaller texture, has become a popular research topic in recent years. Numerous techniques have been proposed to successfully synthesizing 2D textures in terms of quality and performance. 3D or solid texture synthesis, on the other hand, remains relatively unexplored due to its higher complexity. There are several types of existing algorithms for solid texture synthesis, and among them, the outstanding work by Jagnow et al. [1] opens a new door for solid texture synthesis of discrete particles; however, their work did not address two important issues, thus leaving room for further improvement. First, without the help of stereology, users need to explicitly provide the 3D shapes of target particles for synthesis, and this is especially true when oftentimes only a 2D texture image is available for solid texture synthesis. Second, the locations and orientations of the 3D particles are resolved by a simulated annealing method, which is intrinsically a non-deterministic approach, and thus the optimality is not always guaranteed. To solve the shape problem, we propose a simple algorithm that applies the idea of visual hulls to approximate the shapes of 3D particles when only a 2D image is given; to solve the location and orientation problem, we design a deterministic algorithm that could place these desired 3D particles in space more properly. Most importantly, there is no need for user’s intervention for both algorithms. We have successfully implemented the proposed algorithm and the experimental results are also presented for comparisons with previous results and also for the proof of our concepts.