Distribution strategies for very large 3D image deconvolution algorithms

This paper proposes three different distribution strategies for very large 3D image deconvolution algorithms. The deconvolution problem is generic and tailored for spatio-spectral 3D image reconstruction. The three proposed algorithms for large-scale data are distributed in the sense that both the storage and the computations are distributed over several compute nodes. As a result, the workload is drastically reduced compared to a centralized approach where the storage and the computations are handled by a single compute node. The proposed algorithms are validated through experiments on simulated astronomical images.