GPU-accelerated large-size VHR images registration via coarse-to-fine matching
We presented a method for CUDA-accelerated VHR images registration through coarse-to-fine matching. A self-adaptive triangle scan line filling method is developed for efficiently rectification image adapts to local distortion by linear mapping function. Image rectification using CUDA is implemented and it can increases the speed of image rectification by about 40 times. If considering the memory copy time, speed can still be increased by more than 16 times.
image registration coarse-to-fine remote sensing image compute unified device architecture