GPU-accelerated MRF segmentation algorithm for SAR images

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• 作者：Haigang Sui^a ; Feifei Peng^a ; ^b ; Chuan Xu^a ; ^{xc992002@foxmail.com} ; Kaimin Sun^a ; Jianya Gong^a
• 关键词：GPU ; GPGPU ; CUDA ; SAR image segmentation ; MRF
• 刊名：Computers and Geosciences
• 出版年：2012
• 期刊代码：16_00983004
• 类别：ear
• 出版时间：June, 2012
• 卷：43
• 期：Complete
• 页码：159-166
• 文件大小：1451 K

摘要

Markov Random Field (MRF) approaches have been widely studied for Synthetic Aperture Radar (SAR) image segmentation, but they have a large computational cost and hence are not widely used in practice. Fortunately parallel algorithms have been documented to enjoy signi铿乧ant speedups when ported to run on a graphics processing units (GPUs) instead of a standard CPU. Presented here is an implementation of graphics processing units in General Purpose Computation (GPGPU) for SAR image segmentation based on the MRF method, using the C-oriented Compute Unified Device Architecture (CUDA) developed by NVIDIA. This experiment with GPGPU shows that the speed of segmentation can be increased by a factor of 10 for large images.