Efficient screen-space approach to high-quality multiscale ambient occlusion

摘要

We present a new screen-space ambient occlusion (SSAO) algorithm that improves on the state-of-the-art SSAO methods in both performance and quality. Our method computes ambient occlusion (AO) values at multiple image resolutions and combines them to obtain the final, high-resolution AO value for each image pixel. It produces high-quality AO that includes both high-frequency shadows due to nearby, occluding geometry and low-frequency shadows due to distant geometry. Our approach only needs to use very small sampling kernels at every resolution, thereby achieving high performance without resorting to random sampling. As a consequence, our results do not suffer from noise and excessive blur, which are common of other SSAO methods. Therefore, our method also avoids the expensive, final blur pass commonly used in other SSAO methods. The use of multiple resolutions also helps reduce errors that are caused by SSAO's inherent lack of visibility checking. Temporal incoherence caused by using coarse resolutions is solved with an optional temporal filtering pass. Our method produces results that are closer to ray-traced solutions than those of any existing SSAO methods, while running at similar or higher frame rates than the fastest ones.