In recent years, image-based anti-aliasing techniques have been widely investigated in real-time computer graphics. Compared to traditional routine of anti-aliasing, image-based methods, which combined with deferred s...In recent years, image-based anti-aliasing techniques have been widely investigated in real-time computer graphics. Compared to traditional routine of anti-aliasing, image-based methods, which combined with deferred shading, can efficiently decouple anti-aliasing step from standard graphics pipeline. However, most of the existing image-based methods consume video memory, bandwidth and computation resources heavily. In this paper, we propose an optimized anti-aliasing method, which can efficiently reduce the multi-sampling rate by a multi-sampling mask. We carefully designed the rendering system to avoid serial execution on branch divergence, by utilizing both modern GPU’s features and latest shader model. Experimental results demonstrate that our method can achieve high-quality synthesized image with real-time performance.展开更多
基金Supported by National Natural Science Foundation of China(NSFC)(61232014,61421062,61472010)National Key Technology R&D Program of China(2015BAK01B06)+1 种基金National Marine Public Service Project(201505014)Equipment Development Project(315050501)
文摘In recent years, image-based anti-aliasing techniques have been widely investigated in real-time computer graphics. Compared to traditional routine of anti-aliasing, image-based methods, which combined with deferred shading, can efficiently decouple anti-aliasing step from standard graphics pipeline. However, most of the existing image-based methods consume video memory, bandwidth and computation resources heavily. In this paper, we propose an optimized anti-aliasing method, which can efficiently reduce the multi-sampling rate by a multi-sampling mask. We carefully designed the rendering system to avoid serial execution on branch divergence, by utilizing both modern GPU’s features and latest shader model. Experimental results demonstrate that our method can achieve high-quality synthesized image with real-time performance.
