Abstract
Coded aperture snapshot spectral imager (CASSI) provides a potential solution to recover the 3D hyperspectral image (HSI) from a single 2D measurement. The latest proposed design of the dual-camera compressive hyperspectral imager (DCCHI) can collect more information simultaneously with the CASSI to improve the reconstruction quality. The main bottleneck now lies in the high computation complexity of the reconstruction methods, which hinders the practical application. In this paper, we propose a fast parallel implementation based on DCCHI to reach a stable and efficient HSI reconstruction. Specifically, we develop a new optimization method for the reconstruction problem, which integrates the alternative direction multiplier method with the total variation-based regularization to boost the convergence rate. Then, to improve the time efficiency, a novel parallel implementation based on GPU is proposed. The performance of the proposed method is validated on both synthetic and real data. The experimental results demonstrate that our method has a significant advantage in time efficiency, while maintaining a comparable reconstruction fidelity.
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