Hyper-spectral image reconstruction based on SL0-SL0 minimization

Abstract

This paper proposes a new prior image constrained compressive sampling (PICCS) method to reconstruct hyper-spectral images, namely SL0-SL0 minimization-based hyper-spectral imaging (HSI). This is a band-by-band reconstruction method, which reconstructs each hyper-spectral band based on the previous one. This method utilizes not only the sparsity of each hyper-spectral band in certain bases but also the similarity between two consecutive bands. In addition, compared with the popular approaches which reconstruct all the hyper-spectral bands simultaneously, SL0-SL0 minimization-based HSI reduce the requirements to computational ability and memory of receivers for that only one hyper-spectral band is reconstructed at each time. Compared with the exiting PICCS methods, which lose efficiency to reconstruct signals with large size, the SL0-SL0 minimization method significantly speeds up the reconstruction procedure. Some simulations are provided to illustrate the effectiveness of the proposed method.