摘要
传统的Kirsch边缘检测算法的优化和实现都是针对常用处理器提出的。根据Kirsch算法的可并行计算的特点,本文提出了一种基于图形处理器GPU的快速Kirsch算法。快速算法根据GPU的并行结构和硬件特点,采用了纹理存储技术、多点访问技术和对称计算技术三种加速技术,优化了数据存储结构,提高了数据访问效率,降低了算法复杂度。实验表明,采用基于GPU的算法可将对图像的处理速度提高到传统Kirsch边缘检测算法的10倍以上。
The traditional Kirsch edge detection algorithms for optimization and implementation which were designed for common processor.According to parallel computing capability of Kirsch algorithm,a fast Kirsch edge detection algorithm is presented based on GPU.On the basis of the parallel architecture and hardware characteristic of GPU,the fast algorithm introduces three methods to improve the implementation performance： Texture Storage technology optimizes the data storage structure,multiple point access technology improves the data access efficiency,and symmetry computation technology reduces the computation complex.The experiment expressed that we could get a over ten times speed effect by this method than traditional Kirsch algorithm.
出处
《中国科技信息》
2012年第22期83-84,共2页
China Science and Technology Information
基金
漳州职业技术学院科研计划资助项目
项目编号:ZZY1107
