Indian Journal of Science and Technology
DOI: 10.17485/ijst/2013/v6i3.4
Year: 2013, Volume: 6, Issue: 3, Pages: 1-5
Original Article
Aidin Gharahdaghi1* and Omid Pakdelazar2
1 Amirkabir University of Technology (AUT), [email protected]
2 Department of Electrical and Electronic Engineering, [email protected]
*Author For Correspondence
Aidin Gharahdaghi
Department of Electrical and Electronic Engineering
Email:[email protected]
In this paper, we present a method for deconvolution of VLBI images based on both maximum entropy and compressive sensing concepts. The parameters of hybrid method are set optimally by utilization of particle swarm optimization (PSO) algorithm. The proposed method is also used to recover source image in a simulated VLBI. The capability of the proposed hybrid method in recovering the main information of target images of astronomical object is shown when the initial measurement data has limited quality. The main advantage of using such hybrid methods together with optimization is to take advantages from various methods in an integrated system. Keywords: Very Long Baseline Interferometry, Maximum Entropy Method, Compressive Sensing, Particle Swarm Optimization.
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