随着数据采集设备的发展,数字地形分析中高分辨率数字高程模型(DEM)图像越来越普遍。目前已经存在一系列的曲线结构提取算法由于计算复杂度较高,因此在针对高分辨率DEM图像提取地形特征线时效率较低。提出一种在图形处理器(GPU)上加速Steger曲线结构提取算法的策略,利用图形处理器上计算统一设备架构(CUDA)的高度并行性来加速算法中计算密集的Hessian矩阵生成模块以及图像特征点提取模块,对于百万像素级的DEM图像该算法可以获得5倍以上的加速比。

High resolution digital elevation models (DEM) used in digital terrain analysis are becoming more and more prevalent. There are various curvilinear structure extracting algorithms, but the main limitation of them is the high computing cost, making them less efficient when extracting topographic feature lines from high resolution DEM images. We propose an efficient strategy to speed them up using Steger's curvilinear structure detection algorithm imple mented on graphic processing units (GPU). We choose to speed up the most computation intensive modules of the algorithm (Hessian matrix generation and feature point detection) using NVIDIA's compute unified device architecture (CUDA). This method can achieve more than five times speedup compared with the original algorithm on central process units (CPU) for large scale DEM images with millions of pixels.