计算机科学 ›› 2014, Vol. 41 ›› Issue (5): 14-19.doi: 10.11896/j.issn.1002-137X.2014.05.003
何婷婷,芮建武,温腊
HE Ting-ting,RUI Jian-wu and WEN La
摘要： ASIFT(Affine-SIFT)是一种具有仿射不变性、尺度不变性的特征提取算法,其被用于图像匹配中,具有较好的匹配效果,但因计算复杂度高而难以运用到实时处理中。在分析ASIFT算法运行耗时分布的基础上,先对SIFT算法进行了GPU优化,通过使用共享内存、合并访存,提高了数据访问效率。之后对ASIFT计算中的其它部分进行GPU优化,形成GASIFT。整个GASIFT计算过程中使用显存池来减少对显存的申请和释放。最后分别在CPU/GPU协同工作的两种方式上进行了尝试。实验表明,CPU负责逻辑计算、GPU负责并行计算的模式最适合于GASIFT计算,在该模式下GASIFT有很好的加速效果,尤其针对大、中图片。对于2048*1536的大图片,GASIFT与标准ASIFT相比 加速比 可达16倍,与OpenMP优化过的ASIFT相比加速比 可达7倍,极大地提高了ASIFT在实时计算中应用的可能性。
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