Abstract: The Monte Carlo method is the basis of calculating global illumination. Many Monte Carlo-based global illumination algorithms have been proposed. However, most of them have some limitations in terms of rendering time. Based on the Monte Carlo method, a new global illumination algorithm was proposed, combining the Metropolis ray tracing algorithm with an integrated filter. The algorithm is composed of two parts. In the first part, multiple sets of filters with different scales were used to smooth the image; in the second part, filtered images were combined into the final result. Relative Mean Squared Error (RMSE) was used as a basis for the selection of filtering scale, and an appropriate filter was adaptively selected for each pixel during the process of sampling and reconstruction, aiming to reduce the errors to a minimum degree and gain better reconstruction results. Experimental results show that the proposed method outperforms many traditional Metropolis algorithms in terms of both efficiency and image quality.

Key words: Metropolis algorithm, Monte Carlo method, ray tracing, integrated filter, global illumination algorithm

摘要： 蒙特卡罗方法是计算全局光照的基础，目前已经有很多基于蒙特卡罗的全局光照算法，但大多数算法在渲染时间上都有一定局限性。在蒙特卡罗方法基础上，结合Metropolis光线跟踪算法和组合滤波器，提出一种新的全局光照算法。该算法分为两个部分，首先使用多组不同尺度的滤波器对图像进行处理，然后将多组滤波器处理后的结果组合成最终的结果。该算法使用相对均方根误差作为选择滤波尺度的依据，在采样和重建过程中自适应地为每个像素选择合适的滤波器，以最大化降低误差，得到更好的重建结果。实验结果表明，该算法相对于传统Metropolis算法在效率和图像质量上都有较大提高。

关键词: Metropolis算法, 蒙特卡罗方法, 光线跟踪, 组合滤波器, 全局光照算法