TY  - UNPB
EP  - 3
Y1  - 2013///
SP  - 1
T2  - ICASSP 2013
A1  - Rusu, Cristian
A1  - Dumitrescu, Bogdan
AV  - none
M2  - Vancouver, Canada
ID  - eprints1609
TI  - Stagewise K-SVD to Design Efficient Dictionaries for Sparse Representations 
UR  - http://eprints.imtlucca.it/1609/
N2  - The problem of training a dictionary for sparse representations from a given dataset is receiving a lot of attention mainly due to its applications in the fields of coding, classification and pattern recognition. One of the open questions is how to choose the number of atoms in the dictionary: if the dictionary is too small then the representation errors are big and if the dictionary is too big then using it becomes computationally expensive. In this letter, we solve the problem of computing efficient dictionaries of reduced size by a new design method, called Stagewise K-SVD, which is an adaptation of the popular K-SVD algorithm. Since K-SVD performs very well in practice, we use K-SVD steps to gradually build dictionaries that fulfill an imposed error constraint. The conceptual simplicity of the method makes it easy to apply, while the numerical experiments highlight its efficiency for different overcomplete dictionaries.
KW  - classification
KW  -  coding
KW  -  dataset
KW  -  dictionaries
KW  -  error constraint
KW  -  pattern recognition
KW  -  sparse representations
KW  -  stagewise K-SVD 
ER  -