The demand for efficient communication and data storage is continuously increasing and signal representation and compression are important factors in digital communication and storage systems. This work deals with Frame based signal representation and compression. The emphasis is on the design of frames suited for efficient representation, or for low bit rate compression, of classes of signals. Traditional signal decompositions such as transforms, wavelets, and filter banks, generate expansions using an analysis-synthesis setting. In this thesis we concentrate on the synthesis or reconstruction part of the signal expansion, having a system with no explicit analysis stage. We want to investigate the use of an overcomplete set of vectors, a...
Finding a sparse approximation of a signal from an arbitrary dictionary is a very useful tool to sol...
Fusion frames are collection of subspaces which provide a redundant representation of signal spaces....
Image processing problems have always been challenging due to the complexity of the signal. These pr...
The demand for efficient communication and data storage is continuously increasing and signal repres...
Signal expansions using frames may be considered as generalizations of signal representations based ...
In signal compression we distinguish between lossless and lossy compression. In lossless compression...
Signal expansions using frames may be considered as generalizations of sig-nal representations based...
The equation b = Ax + n where the columns of A form an overcomplete set, i.e. the system is under-de...
Sparse signal processing is a mathematical theory that predicts the possibility of reconstructing th...
A mathematical framework for data representation and for noise reduction is presented in this paper....
A mathematical framework for data representation and for noise reduction is presented in this paper....
The problem of efficient signal communication at low data rates involves, in general, the encoding o...
Besides basis expansions, frames representations play a key role in signal processing. We thus consi...
Good signal representation and the corresponding signal processing algorithms lie at the heart of th...
In this paper, application of sparse representation (factorization) of signals over an overcomplete ...
Finding a sparse approximation of a signal from an arbitrary dictionary is a very useful tool to sol...
Fusion frames are collection of subspaces which provide a redundant representation of signal spaces....
Image processing problems have always been challenging due to the complexity of the signal. These pr...
The demand for efficient communication and data storage is continuously increasing and signal repres...
Signal expansions using frames may be considered as generalizations of signal representations based ...
In signal compression we distinguish between lossless and lossy compression. In lossless compression...
Signal expansions using frames may be considered as generalizations of sig-nal representations based...
The equation b = Ax + n where the columns of A form an overcomplete set, i.e. the system is under-de...
Sparse signal processing is a mathematical theory that predicts the possibility of reconstructing th...
A mathematical framework for data representation and for noise reduction is presented in this paper....
A mathematical framework for data representation and for noise reduction is presented in this paper....
The problem of efficient signal communication at low data rates involves, in general, the encoding o...
Besides basis expansions, frames representations play a key role in signal processing. We thus consi...
Good signal representation and the corresponding signal processing algorithms lie at the heart of th...
In this paper, application of sparse representation (factorization) of signals over an overcomplete ...
Finding a sparse approximation of a signal from an arbitrary dictionary is a very useful tool to sol...
Fusion frames are collection of subspaces which provide a redundant representation of signal spaces....
Image processing problems have always been challenging due to the complexity of the signal. These pr...