Güngör, A.Kopanoğlu, E.Çukur, TolgaGüven, H. E.2018-04-122018-04-122016http://hdl.handle.net/11693/37696Date of Conference: 16-19 May 2016Conference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016In this paper, a Multi-Channel/Multi-Contrast image reconstruction algorithm is proposed. The method, which is based on the Augmented Lagrangian Method uses joint convex objective functions to utilize the mutual information in the data from multiple channels to improve reconstruction quality. For this purpose, color total variation and group sparsity are used. To evaluate the performance of the method, the algorithm is compared in terms of convergence speed and image quality using Magnetic Resonance Imaging data to FCSA-MT, an alternative approach on reconstructing multi-contrast MRI data.TurkishAlternating direction method of multipliersCompressed sensingImage reconstructionSparsityConference Paper10.1109/SIU.2016.7496157