Title :
A generalized uncertainty principle and sparse representation in pairs of bases
Author :
Elad, Michael ; Bruckstein, Alfred M.
Author_Institution :
Dept. of Comput. Sci., Stanford Univ., CA, USA
fDate :
9/1/2002 12:00:00 AM
Abstract :
An elementary proof of a basic uncertainty principle concerning pairs of representations of RN vectors in different orthonormal bases is provided. The result, slightly stronger than stated before, has a direct impact on the uniqueness property of the sparse representation of such vectors using pairs of orthonormal bases as overcomplete dictionaries. The main contribution in this paper is the improvement of an important result due to Donoho and Huo (2001) concerning the replacement of the l0 optimization problem by a linear programming (LP) minimization when searching for the unique sparse representation.
Keywords :
dynamic programming; minimisation; signal representation; generalized uncertainty principle; linear programming minimization; optimization; orthonormal bases; overcomplete dictionaries; pairs of bases; sparse representation; uniqueness property; Cities and towns; Computer science; Dictionaries; Electronic mail; Image coding; Image processing; Linear algebra; Linear programming; Uncertainty; Vectors;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2002.801410