Fast Level Set Image Segmentation on Graphics Processing Unit
基于GPU的快速Level Set图像分割

Level set methods are powerful tool to segment images, but these algorithms have a large computational burden thus are not suitable for real time processing requirement. In this paper, an new accelerating algorithm of level set method is presented which is implemented on the new generation of graphics processing unit(GPU) instead of on CPU. It first introduced how to implement grid computation for algebraic linear operation and finite difference solution of PDE on GPU by fragment program, and then map the level set solver to GPU. Since GPU is a parallel vector processor for streamed data with big bandwidth for data access, and the result data don't need to be transferred from CPU to GPU for data rendering, so the accelerating algorithm is suitable for real time processing and rendering. In this paper a 2D level set solver for image segmentation was tested with comparison of the performance result between fast marching method and the GPU accelerated method. It shows this method can achieve 60 percent quicker.