The authors propose a system for the detection of mammographic calcifications. Their method first segments the image into suspected calcification regions and then classifies each detected region as calcification or no...
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The authors propose a system for the detection of mammographic calcifications. Their method first segments the image into suspected calcification regions and then classifies each detected region as calcification or normal background. The segmentation method exploits new local thresholding and region growing techniques suitable for the detection of small blobs in a textured background. The next step of processing is to decrease the number of falsely detected blobs obtained in the first step using pattern recognition techniques. Seven features of the detected regions are used for classification of the segmented region. A quadratic classifier was used to classify mammographic calcification using the region's features. The results of the experimental study using a set of 20 mammographic images shows that the proposed system has a good capability to detect calcifications in mammographic images.< >
The conventional matched filter forms the basis for SAR image generation. Although the impulse response function obtained by the matched filter approach has the best achievable signal-to-noise ratio, high sidelobes, p...
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The conventional matched filter forms the basis for SAR image generation. Although the impulse response function obtained by the matched filter approach has the best achievable signal-to-noise ratio, high sidelobes, paired echoes and azimuth ambiguities will appear in the impulse response function (IRF) for severe phase and amplitude errors. This paper considers two types of error: 1) SAR transceiver chain errors and instabilities which influence the range IRF and 2) azimuth signal aliasing which leads to azimuth ambiguities. In order to suppress these errors and to improve the SAR image quality, an ideal filter concept is used which provides, in addition to the matched filtering, the deconvolution of the phase and amplitude errors. Several simulation results are presented concerning the improvement of the range and azimuth IRFs. In the case of range compression, the sidelobes can efficiently be suppressed if the replica of the transmitted signal is known with sufficient accuracy. For azimuth processing, the Doppler parameters' accuracy and the azimuth fading limits the efficiency of ambiguity suppression. The results of the image quality analysis show that the sidelobes of the IRF obtained by matched filtering are attenuated by more than 10 dB when using the ideal filter concept.
Describes a new class of algorithms for active noise control (ANC) for use in environments in which impulsive noise is present. The well known filtered-x and filtered-U ANC algorithms are designed to minimize the vari...
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Describes a new class of algorithms for active noise control (ANC) for use in environments in which impulsive noise is present. The well known filtered-x and filtered-U ANC algorithms are designed to minimize the variance of a measured error signal. For impulsive noise, which can be modeled using non-Gaussian stable processes, these standard approaches are not appropriate since the second order moments do not exist. The authors propose a new class of adaptive algorithms for ANC that are based on the minimization of a fractional lower order moment, p<2. By studying the effect of p on the convergence behavior of adaptive algorithms, they observe that superior performance is obtained by choosing p/spl ap//spl alpha/ where /spl alpha/<2 is a parameter reflecting the degree of impulsiveness of the noise. applications of this approach to noise cancellation in a duct are presented.
With the objective of using a radar transmitting in the x-band as an oceanographic instrument, it appears necessary to develop methods intended to retrieve the characteristics of a sea surface from the signal received...
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With the objective of using a radar transmitting in the x-band as an oceanographic instrument, it appears necessary to develop methods intended to retrieve the characteristics of a sea surface from the signal received by the radar. A fast method of processing of marine radar images is presented. It is proposed to use a three-dimensional parametric method taking account of the temporal distortion of the sea image introduced by reception of the radar signal as well as the polar form of the pixels of a radar image. Thanks to a series of polar autoregressive parameters and possibly others, it will be possible to retrieve the characteristics of the observed sea surface and to deduce the sea state.
The wavelet transform is a relatively new approach to data processing which has been applied in different areas such as signal, speech and imageprocessing. In the last decade, many papers have been published on wavel...
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The wavelet transform is a relatively new approach to data processing which has been applied in different areas such as signal, speech and imageprocessing. In the last decade, many papers have been published on wavelet theory and its applications. The wavelet transform provides an elegant alternative to the classical Fourier or Gabor transforms unifying numerous signalprocessing techniques in a common framework. The purpose of the present paper is to provide an overview of the applicability of the wavelet transform to EEG signal analysis. In the first part of the paper the mathematical background is summarized. In the second part, applications to the sleep EEG field are presented and discussed. The results of these illustrations demonstrate the usefulness of the wavelet transform to solve various problems including signal parametrization, pattern recognition and biosignal representation.
Malvar wavelets or lapped orthogonal transform has been recognized as a useful tool in eliminating block effects in transform coding. Suter and Oxley extended the Malvar wavelets to more general forms, which enable on...
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ISBN:
(纸本)0819416274;9780819416278
Malvar wavelets or lapped orthogonal transform has been recognized as a useful tool in eliminating block effects in transform coding. Suter and Oxley extended the Malvar wavelets to more general forms, which enable one to construct an arbitrary orthonormal basis on different intervals. In this paper, we generalize the idea in Suter and Oxley from 1D to 2D cases and construct nonseparable Malvar wavelets, which is potentially important in multidimensional signal analysis. With nonseparable Malvar wavelets, we then construct nonseparable Lemarie-Meyer wavelets which are band-limited.
The construction of smooth, orthogonal compactly supported wavelets is accomplished using fractal interpolation functions and splines. These give rise to multiwavelets. In the latter case piecewise polynomial wavelets...
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ISBN:
(纸本)0819416274;9780819416278
The construction of smooth, orthogonal compactly supported wavelets is accomplished using fractal interpolation functions and splines. These give rise to multiwavelets. In the latter case piecewise polynomial wavelets are exhibited using an intertwining multiresolution analysis.
Recently, we demonstrated the use of orthonormal wavelets as desirable waveforms for baseband waveform coding application in digital communications. In this paper, we examine the use of generalized biorthogonal wavele...
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ISBN:
(纸本)0819416274;9780819416278
Recently, we demonstrated the use of orthonormal wavelets as desirable waveforms for baseband waveform coding application in digital communications. In this paper, we examine the use of generalized biorthogonal wavelets for waveform coding. Though the transmit and receive waveforms have different supports in the biorthogonal case, it is shown that binary symbols can be extracted easily at the receiver. Spectral characteristics of several types of biorthogonal wavelets are examined and resulting codecs' bandwidth efficiencies (in bits/sec/Hz) are provided. An M-band wavelet codec is also proposed. Preliminary results indicate that the M-band codec (used in this study) will be out-performed by a two-band codec of the same order.
We present in the following work, a multiscale edge detection algorithm whose aim is to detect edges of any slope. Our work is based on a generalization of the Canny-Deriche filter, modelized by a more realistic edge ...
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ISBN:
(纸本)0819416274
We present in the following work, a multiscale edge detection algorithm whose aim is to detect edges of any slope. Our work is based on a generalization of the Canny-Deriche filter, modelized by a more realistic edge than the traditional step shape edge. The filter impulse response is used to generate a frame of wavelets. For the merging of the wavelet coefficients, we use a geometrical classifier developed in our laboratory. The segmentation system thus set up and after the training phase does not require any adjustment nor parameter. The main original property of this algorithm is that it leads to a binary edge image without any threshold setting.
Unlike the classical wavelet decomposition scheme it is possible to have different scaling and wavelet functions at every scale by using non-stationary multiresolution analyses. For the bidimensional case inhomogeneou...
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ISBN:
(纸本)0819416274
Unlike the classical wavelet decomposition scheme it is possible to have different scaling and wavelet functions at every scale by using non-stationary multiresolution analyses. For the bidimensional case inhomogeneous multiresolution analyses using different scaling and wavelet functions for the two variables are introduced. Beyond it, these two methods are combined. All this freedom is used for compact image coding. The idea is to build out of the functions in a library that special non-stationary and/or inhomogeneous multiresolution analysis, that is best suited for a given image in the context of compact coding (in the sense of optimizing certain cost-functions).
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