基于GPU的快速Sobel边缘检测算法

Fast Sobel Edge Detection Algorithm Based on GPU

传统的Soble边缘检测算法的优化和实现都是针对常用处理器(CPU、DSP和FPGA等)提出的,难以应用在图像处理器(GPU)上。本文提出了一种基于NVIDIA公司CUDA架构图形处理器(GPU)的快速Sobel边缘检测算法。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。实验结果表明,快速算法充分利用了GPU的并行处理能力,在处理4096×4096分辨力的8位灰度图像时速度可达190fps,是基于CPU实现的122倍。

The traditional Soble edge detection algorithms for optimization and implementation which were designed for common processor such as CPU, DSP and FPGA, could not be effectively applied on Graphics Processor Unit （GPU）. A fast Sobel edge detection algorithm is presented based on NVIDA＇s GPU which support Compute Unified Device Architecture （CUDA）. 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 result shows that GPU can effectively implement the fast algorithm and processing speed of 8-bit 4 096×4 096 pictures can be up to 190 fps, which is 122 times faster than CPU-based implementation.