Open AccessGPU-accelerated compressive holography
Author(s) -
Yutaka Endo,
Tomoyoshi Shimobaba,
Takashi Kakue,
Tomoyoshi Ito
Publication year - 2016
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.24.008437
Subject(s) - graphics processing unit , computer science , holography , compressed sensing , digital holography , cuda , graphics , computational science , thresholding , parallel computing , central processing unit , matrix (chemical analysis) , general purpose computing on graphics processing units , sparse matrix , algorithm , iterative reconstruction , computer graphics (images) , optics , computer vision , image (mathematics) , computer hardware , physics , materials science , composite material , quantum mechanics , gaussian
In this paper, we show fast signal reconstruction for compressive holography using a graphics processing unit (GPU). We implemented a fast iterative shrinkage-thresholding algorithm on a GPU to solve the ℓ 1 and total variation (TV) regularized problems that are typically used in compressive holography. Since the algorithm is highly parallel, GPUs can compute it efficiently by data-parallel computing. For better performance, our implementation exploits the structure of the measurement matrix to compute the matrix multiplications. The results show that GPU-based implementation is about 20 times faster than CPU-based implementation.