GPU-CPU Cooperate Processing of RS Image Ortho-Rectification

A fast ortho-rectification GPU-CPU cooperate processing algorithm is presented based on compute unified device architecture(CUDA),which realizes fine-grained parallel re-sampling using GPU in single instruction multiple thread(SIMT) pattern.On the basis of parallel architecture and hardware characteristic of GPU,the parallel algorithm introduces three speedup methods to improve the implementation performance: using execution configuration optimize technology to increase warp occupancy,using shared memory to reduce coordinate transform coefficients accessing times of low-speed global memory,using texture memory replace global memory to optimize the accessing of original image.The experiment result shows that using GeForce 9500 GT display-card to do multinomial rectification for gray image size of 6 000 pixel×6 000 pixel,the speed is more than 8 times and 10 times faster than CPU-based implementation each for nearest-neighbor interpolation and bilinear interpolation.