Rutger L. van Spaendonck

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Complex discrete wavelet transforms have significant advantages over real wavelet transforms for certain signal processing problems. Two approaches to the implementation of complex wavelet transforms have been proposed earlier. Both approaches require discrete-time allpass systems having approximately linear-phase and (fractional) delay. This paper compares(More)
Complex wavelet transforms offer the opportunity to perform directional and coherent processing based on the local magnitude and phase of signals and images. Although demising, segmentation, and image enhancement are significantly improved using complex wavelets, the redundancy of most current transforms hinders their application in compression and related(More)
Although the discrete wavelet transform (DWT) is a powerful tool for signal and image processing, it has three serious disadvantages: shift sensitivity, poor directionality, and lack of phase information. To overcome these disadvantages, we introduce multidimensional, mapping-based, complex wavelet transforms that consist of a mapping onto a complex(More)
Shift variance and poor directional selectivity, two major disadvantages of the discrete wavelet transform, have previously been circumvented either by using highly redundant, non-separable wavelet transforms or by using restrictive designs to obtain a pair of wavelet trees with a transform-domain redundancy of 4.0 in 2D. In this paper, we demonstrate that(More)
Poor directional selectivity, a major disadvantage of the 2D separable discrete wavelet transform (DWT), has heretofore been circumvented either by using highly redundant, nonseparable wavelet transforms or by using restrictive designs to obtain a pair of wavelet trees. In this paper, we demonstrate that superior directional selectivity may be obtained with(More)
Time-frequency distributions have proven to be a powerful tool to get more insights in seismic data (Steeghs, 1997). For seismic characterization a signal can be described in a combined time-frequency domain and as such it can be used for identi cation and characterization of certain stratigraphic sequences and fault patterns (Steeghs, 1997). There are many(More)
Shift variance and poor directional selectivity, two major disadvantages of the discrete wavelet transform, have previously been circumvented either by using highly redundant, non-separable wavelet transforms or by using restrictive designs to obtain a pair of wavelet trees with a transform-domain redundancy of 4.0 in 2D. In this paper, we demonstrate that(More)
The complex trace attributes are widely used in seismic interpretation. These attributes are based on the properties of the analytic signal. The analytic signal is usually computed through the Fourier transform. This transform has a global character and hence is not fit for characterization of local signal parameters. We have developed a local(More)
Shift sensitivity, poor directional selectivity and lack of phase information are three major disadvantages of the discrete wavelet transform, In earlier research, we demonstrated that projection-based complex wavelet transforms have excellent directional selectivity and explicit phase information, In this paper, we discuss the theory of projection-based(More)