Parallel implementation of a hyperspectral unmixing chain: Graphic processing units versus multi-core processors

Abstract

Spectral unmixing is an important tast for remotely sensed hyperspectral imaging. Spectral unmixing algorithms can be computationally expensive. In this paper, we develop two efficient implementations of a full hyperspectral unmixing chain on two different kinds of high performance computing architectures: graphics processing units (GPUs) and multi-core processors. These platforms are inter-compared in the context of hyperspectral unmixing. Our experimental results reveal that both GPUs and multi-core processors can provide real-time unmixing performance when properly implemented in this kind of parallel platforms.