In this paper we present a new nonlinear fuzzy filter for imageprocessing in a mixed noise environment, where both additive Gaussian noise and non-additive impulsive noise may be present. Averaging filters can effect...
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ISBN:
(纸本)0780318978
In this paper we present a new nonlinear fuzzy filter for imageprocessing in a mixed noise environment, where both additive Gaussian noise and non-additive impulsive noise may be present. Averaging filters can effectively remove the Gaussian noise and order statistics filters or median filters can effectively remove the impulsive noise. However, it is difficult to combine these filters to remove mixed noise in an imaging processing environment without blurring the image details or edges. Trying to distinguish between noise and edge information in the image is an inherently ambiguous problem and naturally leads to the development of a fuzzy filter. We use local statistics to train the membership function of a fuzzy filter for imageprocessing to remove both Gaussian noise and impulsive noise while preserving edges. We show that such a fuzzy filter gives superior results compared to averaging filters, median filters, and other fuzzy filters. We also demonstrate the robustness of this filtering technique.
An analogy is made between each straight line in an image and a planar propagating wavefront impinging on an array of sensors so as to obtain a mathematical model exploited in recent high resolution methods for direct...
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An analogy is made between each straight line in an image and a planar propagating wavefront impinging on an array of sensors so as to obtain a mathematical model exploited in recent high resolution methods for direction-of-arrival estimation in sensor array processing. The new so-called SLIDE (Subspace-Based Line Detection) algorithm then exploits the spatial coherence between the contributions of each line in different rows of the image to enhance and distinguish a signal subspace that is defined by the desired line parameters. SLIDE yields closed-form and high resolution estimates for line parameters, and its computational complexity and storage requirements are far less than those of the standard method of the Hough transform. If unknown a priori, the number of lines is also estimated in the proposed technique. The signal representation employed in this formulation is also generalized to handle grey-scale images as well. The technique has also been generalized to fitting planes in 3-D images. Potential application areas of the proposed technique include road tracking in robotic vision, mask-wafer alignment and linewidth measurement in semiconductor manufacturing, aerial image analysis, text alignment in document analysis, particle tracking in hubble chambers, and similar applications.
The article describes a generalizable method for creating hybrid computational architectures. This method, based on a metaphor of biological symbiosis, provides a systematic approach to combining attributes of dispara...
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The paper describes the use of a genetically controlled automaton model to tackle imageprocessing problems. A generalised system is set up that attempts to discover the precise cellular automaton functions required t...
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The paper reports a region-based coding scheme for segmented textured images. The proposed approach uses basic principles of transform image coding which are generalized for the case of arbitrarily shaped image segmen...
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In this paper, we define a novel system based on a hierarchical computational and data abstraction model to handle multimedia queries involving face recognition, scene matching, and speech recognition. For this purpos...
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We introduce the speech processing technology being studied and developed in Korea as well as its current status, problems, and future prospects. Time-varying and nonlinear methods will play important roles in the fut...
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The paper presents a new method for detection and tracking of pixel-sized moving targets from a time sequence. It uses the pipeline continuity filter for preprocessing, and then tracks the target trajectories in the t...
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Artificial neural networks (ANNs) are widely used on many research fields because of their high speed for execution and low cost for hardware implementation. In the paper, ANNs are used in fractal image compression be...
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The paper presents a Kalman filter based centroid tracking approach for multiple small targets. Before targets overlap, each target is tracked by a Kalman filter. When two targets overlap, a merged target is formed, a...
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