An empirical measure for the selection of the edge-enhancement Gaussian filter is developed. The Gaussian filter is specified by its standard deviation sigma ; the filter's spatial support is a function of sigma ....
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An empirical measure for the selection of the edge-enhancement Gaussian filter is developed. The Gaussian filter is specified by its standard deviation sigma ; the filter's spatial support is a function of sigma . An estimation procedure for sigma using Fourier analysis is described. The measure is easy to implement and is based totally on the image at hand. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter's spatial support, which is needed to enhance the edges. Other equivalent bandwidth definitions can be used to obtain a measure of the frequency spread in the smoothed image (e.g., the mean-square bandwidth).< >
According to the Floquet theory, an nth-order linear periodic (LP) system of the form yn+αn(t) y/sup n-1/+...+α2(t)dy(t)/dt+α1(t)y=0 can be transformed into an equivalent linear time-invariant (LTI) system whose ch...
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An integrated adaptive fuzzy clustering (IAFC) algorithm using a structure similar to that found in the Adaptive Resonance Theory (ART-1) neural network, is presented. The IAFC incorporates a new learning rule and a n...
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An integrated adaptive fuzzy clustering (IAFC) algorithm using a structure similar to that found in the Adaptive Resonance Theory (ART-1) neural network, is presented. The IAFC incorporates a new learning rule and a new similarity measure to eliminate some structural problems inherent in other fuzzy ART-type neural networks. The new learning rule utilizes a fuzzy membership value, a function of the number of iterations, and a fuzzy within-cluster membership value. The new similarity measure incorporates a fuzzy membership value to the Euclidean distance. This incorporation of the new learning rule and the new similarity measure guarantees the convergence of weights in the IAFC algorithm and provides more flexibility to the shapes of the clusters formed by this algorithm. The critical parameters in the operation of IAFC are discussed. The performance of IAFC is evaluated in the classification of real data and compared with other recent neuro-fuzzy clustering algorithms.< >
A new direct contrast enhancement algorithm is proposed. It can be used to enhance the contrast of an image without increasing the dynamic range of the pixel values. A distinctive property of the proposed method is th...
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A new direct contrast enhancement algorithm is proposed. It can be used to enhance the contrast of an image without increasing the dynamic range of the pixel values. A distinctive property of the proposed method is that it yields results matching the characteristic of the human visual system. The histogram of the enhanced image has almost the same shape as that of the original image.< >
A general approach to the transform-magnitude-shaping-based image enhancement method is advanced. In the method, the magnitude of the input image transform is modified using a nonlinear mapping expressible as a power ...
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A general approach to the transform-magnitude-shaping-based image enhancement method is advanced. In the method, the magnitude of the input image transform is modified using a nonlinear mapping expressible as a power series, while its phase is kept invariant. The inverse transform of the modified image transform results in a sharpening or smoothing depending on the choice of the power series coefficients. Further improvement in the overall enhancement is achieved by a two-channel processing scheme which is implemented by applying different transform amplitude shaping methods to the low-frequency and high-frequency components. Examples the proposed enhancement method are included.< >
It is well-known that the stability of linear periodic (LP) systems can be assessed using Floquet Characteristic Exponents (FCE). In this paper, a new method is presented for evaluating FCE for nth-order scalar period...
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It is well-known that the stability of linear periodic (LP) systems can be assessed using Floquet Characteristic Exponents (FCE). In this paper, a new method is presented for evaluating FCE for nth-order scalar periodic linear systems based on a recently developed unified eigenvalue theory for linear time-varying (LTV) Systems [1]. The new theory allows FCEs to be evaluated from the DC term of the Fourier series of periodic PD-eigen-values of a LP system. Comparing to the well-known Monodromy Matrix (MM) method and Infinite Dimensional Determinant (IDD) method for evaluating FCE 1 the solutions obtained by the new method have rapid local convergence. This new method also allow stability boundaries in the parameter space of a LP system to be evaluated and plotted directly. The new results shed some light OL the general stability assessment problem for vector periodic linear systems and aperiodic LTV systems. Further studies along this direction are also discussed in this paper.
For real-time radar processing, it is very desirable to have an algorithm that does not assume restricted statistics of the input data and can be implemented for high-speed processing (without a high cost) to meet rea...
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For real-time radar processing, it is very desirable to have an algorithm that does not assume restricted statistics of the input data and can be implemented for high-speed processing (without a high cost) to meet real-time requirements. We therefore apply the QR decomposition-based least-squares method for linear prediction to the problem of computing the reflection coefficients of a lattice predictor, instead of using the conventional Burg algorithm. We also propose a modified one-dimensional ring architecture for implementing the QR method of least-squares. The particular application considered in this case is that of surveillance radar systems for air traffic control.< >
A new class of morphological filters is proposed for image enhancement. The filter, known as the generalized morphological filter (GMF), uses multiple structuring elements and combines linear and morphological operati...
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A new class of morphological filters is proposed for image enhancement. The filter, known as the generalized morphological filter (GMF), uses multiple structuring elements and combines linear and morphological operations. The GMF can be designed to suppress various types of noise yet preserve geometrical structure in an image. A study of several aspects of the performance of the filter is presented. The study includes geometrical feature preservation, noise suppression, structuring element selection, and the root signal structure. For the sake of comparison, averaging and median filters are also used in the experiments and corresponding figures of merit of the performance of the filter. The empirical study shows that the generalized morphological filter possesses effective noise suppression with reduced geometrical feature blurring.
Edge-based image segmentation is a two-stage process;edge enhancement followed by edge linking. Modern approaches for edge enhancement use either the gradient of the Gaussian operator (VG) or the Laplacian of the Gaus...
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Two commonly used optical correlation techniques, matched spatial filtering and joint-Fourier transform correlation, are briefly reviewed. A recently proposed real-time joint-Fourier transform correlation is then disc...
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