The FPSO for selecting number of components in Tucker3 decomposition for Hyperspectral image compression

Hyperspectral images (HSI) contain hundreds of bands, which brings huge amount of data. In this paper, we propose a novel compression method for HSI with Tucker3 decomposition. The hyperspectral images are firstly decomposed into core tensor, and then the number of components is selected according to the Fast particle swarm optimization (FPSO). Compared to the traditional methods, the new method has excellent reconstruction quality and less computing time.