Showing papers by "Ioannis Pitas published in 1986"
TL;DR: It is shown that nonlinear filters based on these means behave well for both additive and impulse noise and they preserve the edges better than linear filters, and they reject the noise better than median filters.
Abstract: The use of nonlinear means in image processing is introduced. The properties of these means in the presence of different types of noise are investigated. It is shown that nonlinear filters based on these means behave well for both additive and impulse noise. Their performance in the presence of signal dependent noise is satisfactory. They preserve the edges better than linear filters, and they reject the noise better than median filters.
191 citations
TL;DR: A class of edge detectors is proposed which is obtained from the difference of the outputs of two nonlinear filters which are based on nonlinear means or order statistic or contain median filters.
Abstract: A class of edge detectors is proposed which is obtained from the difference of the outputs of two nonlinear filters. The nonlinear filters used are based on nonlinear means (which contain homomorphic filters) or order statistic (which contain median filters). The performance of these edge detectors in the presence of noise is evaluated and is compared to the performance of well established edge detectors. Their computational requirements are described and some examples are presented.
70 citations
TL;DR: In this paper, a class of nonlinear filters for image processing is proposed, which is a combination of non-linear mean and order statistic filters, and the properties of these filters in the presence of different kinds of noise are investigated.
69 citations
TL;DR: The present paper relies on the conjugate property of the generalized DFT in order to define novel, advantageous algorithms for the in-place calculation of the DFT of multidimensional sequences.
Abstract: The computation of the discrete Fourier transform (DFT) of real multidimensional sequences requires an extraordinary amount of computer memory. The in-place calculation of the discrete Fourier transform reduces the required memory and is thus highly desirable. The present paper relies on the conjugate property of the generalized DFT in order to define novel, advantageous algorithms for the in-place calculation of the DFT of multidimensional sequences.
5 citations
TL;DR: The aim of this paper is to couple wave theory and detection theory to detect seismic events in an optimal way and to propose a statistical model of the earth which describes sufficiently well the wave propagation in the stratified earth.
Abstract: Event detection is a very important task in geophysics. It encompasses the detection of wave sources (earthquakes, subsurface explosions) and the detection of wave reflectors (interfaces between rock layers having different velocities and/or different densities). The latter application is very important in seismic oil prospecting. Seismic events release energy which propagates toward the earth surface as waves which are recorded by arrays of sensors. The data recorded are usually corrupted by noise, which sometimes is much stronger than the weak events. The aim of this paper is to couple wave theory and detection theory to detect seismic events in an optimal way. A statistical model of the earth is proposed. This model combined with the wave equation describes sufficiently well the wave propagation in the stratified earth. Optimal and suboptimal receivers for event detection, based on this earth model, are proposed. The validity of our approach is demonstrated by simulation examples.
2 citations