A Low Cost Anti-aliasing Scheme for Mobile Devices

Daolu Zha, Xi Jin, An Wu, Tian Xiang, Xueliang Du
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Abstract

An improved anti-aliasing sampling algorithm is submitted to reduce the increasing memory consumption caused by super-sampling in mobile devices. Six-point anisotropy sampling blends the two samples of a pixel, as well as the nearby pixels. Experiment results showed that six-point anisotropy sampling has reduced the memory consumption by 50% than traditional FLIPQUAD anti-aliasing super-sampling algorithm. This method has similar quality to FLIPQUAD with only 50% memory consumption.
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一种低成本的移动设备抗混叠方案
提出了一种改进的抗混叠采样算法,以减少移动设备中由于超采样而增加的内存消耗。六点各向异性采样混合了一个像素的两个样本,以及附近的像素。实验结果表明,六点各向异性采样比传统的FLIPQUAD抗混叠超采样算法减少了50%的内存消耗。该方法具有与FLIPQUAD相似的质量,仅消耗50%的内存。
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