Title :
L0-Norm-Based Sparse Representation Through Alternate Projections
Author :
Mancera, L. ; Portilla, Javier
Author_Institution :
Dept. of Comput. Sci. & Artificial Intelligence, Granada Univ., Spain
Abstract :
We present a simple and robust method for finding sparse representations in overcomplete transforms, based on minimization of the L0-norm. Our method is better than current solutions based on minimization of the L1-norm in terms of energy compaction. These results strongly question the equivalence of minimizing both norms in real conditions. We also show application to in-painting (interpolation of lost pixels).
Keywords :
image representation; L0-norm; sparse representation; Artificial intelligence; Compaction; Computer science; Degradation; Dictionaries; Equations; Information processing; Minimization methods; Robustness; Vectors; Image representation; restoration;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312819
