A MPI-based parallel pyramid building algorithm for large-scale remote sensing images

Building pyramids for remote sensing (RS) image is an effective way to achieve image multi-resolution organization, and also an important way to improve the performance of image browsing. For large-scale remote sensing images, traditional sequential pyramid building processing is a time consuming task in many applications. By taking advantage of multi-core, multi-node cluster computing environments and parallel processing mechanisms, a MPI (Message Passing Interface)-based parallel algorithm is proposed, which can greatly improve the performance of pyramid building. The algorithm has a good scalability and can easily be extended to a considerable number of nodes. Experimental results show that the proposed algorithm has a better acceleration effect compared to the sequential methods, and there is a positive correlation between the acceleration effect and image size. For large remote sensing images (in our case 46 GB), the parallel algorithm can be about 10 times faster than GDAL.