Signal Processing 30 ( 1993 ) 135 136 135 Elsevier Thesis alerts Touradj Ebrahimi* Perceptually derived localized linear operators" Application to image sequence compression Signal Processing Laboratory, Swiss Federal Institute of" Technology ( EPFL), Lausaune, Switzerland The theory of linear operators covers a large number of applications in applied mathematics and signal processing. This thesis discusses three commonly used linear operators, namely the short time Fourier transform, the wavelet decomposition and the subband decomposition. Common features and differences between the above operators are exam- ined in the framework of image sequence compression. In particular, the Gabor expansion, as a special case of short time Fourier transform, is discussed in detail. A new and efficient technique to perform Gabor expansion of signals is introduced. A comparative study between the above approach and other commonly used techniques for Gabor expansion of signals is given in terms of computational complexity. The subband decomposition of signals and the wavelets theory are two sub-classes of linear operators which were devel- oped in two different disciplines. However, there exist big similarities between the two approaches. After a brief introduction of subband decomposition and wavelet theory, the equivalence and differences between them are discussed, in both * Thesis Advisor: Murat Kunt, June 1992. orthonormal and biorthonormal cases. The multiresolution representation of data is considered in particular. A new approach to filter bank design in time domain, using matrix formulation is introduced. Using this approach, an efficient filter bank with low complexity and good frequency response is designed. The characteristics of this filter bank are compared with that of other commonly used short kernel filter banks, for video compression applications. The generic coding is an important component in any modern communication system. In this thesis, a generic video codec is introduced which is able to compress efficiently image sequences with any format at desired bit-rate, without any change in its architecture. The approach is based on multiresolution representation of data, which is generated by the filter bank proposed in this work. The use of multiresolution data structure in conjunction with other compo- nents of the system such as multiresolution motion estimation allows a simple and efficient implemen- tation. Simulations on typical image sequences show that it is possible to perform generic coding with reduced complexity and good efficiency. Elsevier Science Publishers B.V.

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Signal Processing 30 ( 1993 ) 135 136 135 Elsevier

Thesis alerts

Touradj Ebrahimi*

Perceptually derived localized linear operators" Application to image sequence compression Signal Processing Laboratory, Swiss Federal Institute of" Technology ( EPFL), Lausaune, Switzerland

The theory of linear operators covers a large number of applications in applied mathematics and signal processing. This thesis discusses three commonly used linear operators, namely the short time Fourier transform, the wavelet decomposition and the subband decomposition. Common features and differences between the above operators are exam- ined in the framework of image sequence compression. In particular, the Gabor expansion, as a special case of short time Fourier transform, is discussed in detail. A new and efficient technique to perform Gabor expansion of signals is introduced. A comparative study between the above approach and other commonly used techniques for Gabor expansion of signals is given in terms of computational complexity. The subband decomposition of signals and the wavelets theory are two sub-classes of linear operators which were devel- oped in two different disciplines. However, there exist big similarities between the two approaches. After a brief introduction of subband decomposition and wavelet theory, the equivalence and differences between them are discussed, in both

* Thesis Advisor: Murat Kunt , June 1992.

orthonormal and biorthonormal cases. The multiresolution representation of data is considered in particular. A new approach to filter bank design in time domain, using matrix formulation is introduced. Using this approach, an efficient filter bank with low complexity and good frequency response is designed. The characteristics of this filter bank are compared with that of other commonly used short kernel filter banks, for video compression applications. The generic coding is an important component in any modern communication system. In this thesis, a generic video codec is introduced which is able to compress efficiently image sequences with any format at desired bit-rate, without any change in its architecture. The approach is based on multiresolution representation of data, which is generated by the filter bank proposed in this work. The use of multiresolution data structure in conjunction with other compo- nents of the system such as multiresolution motion estimation allows a simple and efficient implemen- tation. Simulations on typical image sequences show that it is possible to perform generic coding with reduced complexity and good efficiency.

Elsevier Science Publishers B.V.