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GPU Accelerated FFT-Based Registration of Hyperspectral Scenes

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Registration is a fundamental previous task in many applications of hyperspectrometry. Most of the algorithms developed are designed to work with RGB images and ignore the execution time. This paper… Click to show full abstract

Registration is a fundamental previous task in many applications of hyperspectrometry. Most of the algorithms developed are designed to work with RGB images and ignore the execution time. This paper presents a phase correlation algorithm on GPU to register two remote sensing hyperspectral images. The proposed algorithm is based on principal component analysis, multilayer fractional Fourier transform, combination of log-polar maps, and peak processing. It is fully developed in CUDA for NVIDIA GPUs. Different techniques such as the efficient use of the memory hierarchy, the use of CUDA libraries, and the maximization of the occupancy have been applied to reach the best performance on GPU. The algorithm is robust achieving speedups in GPU of up to ${\text{240}}.{\text{6}}\times$.

Keywords: fft based; gpu accelerated; registration hyperspectral; registration; based registration; accelerated fft

Journal Title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year Published: 2017

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