Evaluation of the graphics processing unit architecture for the implementation of target detection algorithms for hyperspectral imagery

Abstract

Abstract. Recent advances in hyperspectral imaging sensors allow the acquisition of images of a scene at hundreds of contiguous narrow spectral bands. Target detection algorithms try to exploit this high-resolution spectral information to detect target materials present in a scene, but this process may be computationally intensive due to the large data volumes generated by the hyperspectral sensors, typically hundreds of megabytes. Previous works have shown that hyperspectral data processing can significantly benefit from the parallel computing resources of graphics processing units (GPUs), due to their highly parallel structure and the high computational capabilities that can be achieved at relative low costs. We studied the parallel implementation of three target detection algorithms (RX algorithm, matched filter, and adaptive matched subspace detector) for hyperspectral images in order to identify the aspects in the structure of these algorithms that can exploit the CUDA™ architecture of NVIDIA ® GPUs. A data set was generated using a SOC-700 hyperspectral imager to evaluate the performance and detection accuracy of the parallel implementations on a NVIDIA ® Tesla™ C1060 graphics card, achieving real-time performance in the GPU implementations based on global statistics.

The index array approach and the dual tiled similarity algorithm for UAS hyper-spatial image processing

“…Some research has been done in the GPU-based processing of remote sensing imagery. For example, references [4][5][6][7][8][9][10][11][12] explored hyperspectral image processing by the GPU with a focus on handling hundred spectral bands on the same image pixel. References [13][14][15][16][17][18] proposed the GPU methods for geocorrection and orthorectification (also called geo-referencing) for imagery acquired by UAS commercial off-the-shelf cameras, an airborne pushbroom imager, and high resolution satellite sensors.…”