Approximate Message Passing in Coded Aperture Snapshot Spectral Imaging
Abstract
We consider a compressive hyperspectral imaging reconstruction problem, where three-dimensional spatio-spectral information about a scene is sensed by a coded aperture snapshot spectral imager (CASSI). The approximate message passing (AMP) framework is utilized to reconstruct hyperspectral images from CASSI measurements, and an adaptive Wiener filter is employed as a three-dimensional image denoiser within AMP. We call our algorithm "AMP-3D-Wiener." The simulation results show that AMP-3D-Wiener outperforms existing widely-used algorithms such as gradient projection for sparse reconstruction (GPSR) and two-step iterative shrinkage/thresholding (TwIST) given the same amount of runtime. Moreover, in contrast to GPSR and TwIST, AMP-3D-Wiener need not tune any parameters, which simplifies the reconstruction process.
Keywords
Cite
@article{arxiv.1509.02427,
title = {Approximate Message Passing in Coded Aperture Snapshot Spectral Imaging},
author = {Jin Tan and Yanting Ma and Hoover Rueda and Dror Baron and Gonzalo Arce},
journal= {arXiv preprint arXiv:1509.02427},
year = {2015}
}
Comments
to appear in Globalsip 2015