High performance computing for hyperspectral image analysis: Perspective and state-of-the-art
The main purpose of this paper is to describe available (HPC)-based implementations of remotely sensed hyperspectral image processing algorithms on multi-computer clusters, heterogeneous networks of computers, and specialized hardware architectures such as field programmable gate arrays (FPGAs) and graphic processing units (GPUs). Combined, the revision of existing techniques conducted in this paper, along with the description of performance results for a parallel hyperspectral processing chain on different architectures, delivers an excellent snapshot of the state-of-the-art in the area of HPC-based hyperspectral image processing and a thoughtful perspective of the potential and emerging challenges of applying HPC paradigms to hyperspectral imaging problems.