A method is proposed for accelerating remote sensing image filtering in real-time using an embedded CPU + GPU heterogeneous platform for satellite-based image processing.the algorithm was initially parallelized through data division and mapping,leveraging the parallel computing capabilities of the GPU.Subsequently,hardware resources like the vector unit and cache of the GPU were employed to enhance algorithm speed through vectorization,vector permutation,and workgroup tuning.The feasibili-ty and efficiency of this accelerated design were validated on an embedded development board.The ex-periments demonstrate a speedup ranging from 4.08 to 16.92 times when incorporating GPU parallel pro-cessing,compared to the serial implementation on a single CPU.Further optimization using GPU hard-ware resources can push the speedup to 15.38 to 56.41 times.
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