An augmented Lagrangian method for image reconstruction with multiple features

Warning The system is temporarily closed to updates for reporting purpose.

Güven, Emre and Güngör, Alper and Çetin, Müjdat (2015) An augmented Lagrangian method for image reconstruction with multiple features. In: IEEE International Conference on Image Processing (ICIP 2015), Quebec City, QC, Canada

[img]PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader

Official URL: http://dx.doi.org/10.1109/ICIP.2015.7351592


We present an Augmented Lagrangian Method (ALM) for solving image reconstruction problems with a cost function consisting of multiple regularization functions with a data fidelity constraint. The presented technique is used to solve inverse problems related to image reconstruction, including compressed sensing formulations. Our contributions include an improvement for reducing the number of computations required by an existing ALM method, an approach for obtaining the proximal mapping associated with p-norm based regularizers, and lastly a particular ALM for the constrained image reconstruction problem with a hybrid cost function including a weighted sum of the p-norm and the total variation of the image. We present examples from Synthetic Aperture Radar imaging and Computed Tomography.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:Augmented Lagrangian Method, Image Reconstruction, Compressed Sensing, Alternating Direction Method of Multipliers, Sparsity
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:28934
Deposited By:Müjdat Çetin
Deposited On:23 Dec 2015 21:25
Last Modified:23 Aug 2019 15:47

Repository Staff Only: item control page