A real-time approximation algorithm of nonlinear filtering based on image pyramid

Abstract

In the field of real-time rendering, post-processing filters are crucial techniques for achieving global illumination and photorealistic rendering in real-time rasterization and ray tracing rendering pipelines. Due to the power consumption limitations and insufficient memory bandwidth of mobile devices, filters can cause significant performance bottlenecks. To reduce the cost of filters on mobile devices, this paper proposes a real-time approximation method for nonlinear filtering. Our method reduce the number of texture samplings and memory usage. Through experiments conducted on mobile devices, it has been demonstrated that the proposed method can effectively reduce the number of texture samplings in feature images within scenes of similar complexity, as compared to mainstream industrial methods. This reduction in texture samplings leads to improved rendering quality while maintaining the same frame rate. Our method eliminates performance bottlenecks and enhances the quality of global illumination on mobile devices. By reducing the computational complexity of the non-linear filter, it provides users with a smoother experience.