MCALab: Reproducible Research in Signal and Image Decomposition and Inpainting

Morphological Component Analysis (MCA) of signals and images is an ambitious and important goal in signal processing; successful methods for MCA have many far-reaching applications in science and technology. Because MCA is related to solving underdetermined systems of linear equations it might also be considered, by some, to be problematic or even intractable. Reproducible research is essential to to give such a concept a firm scientific foundation and broad base of trusted results. MCALab has been developed to demonstrate key concepts of MCA and make them available to interested researchers and technologists. MCALab is a library of Matlab routines that implement the decomposition and inpainting algorithms that we previously proposed in [1], [2], [3], [4]. The MCALab package provides the research community with open source tools for sparse decomposition and inpainting and is made available for anonymous download over the Internet. It contains a variety of scripts to reproduce the figu...

• Type: Journal
• Year: 2010
• Where: CSE
• Authors: Mohamed-Jalal Fadili, Jean-Luc Starck, Michael Elad, David L. Donoho
• Keywords: CSE 2010, Firm Scientific Foundation, Interested Researchers, Morphological Component Analysis, Theoretical Computer Science