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Selection Weighted Vector Directional Filters
"... In this paper, a class of Weighted Vector Directional Filters (WVDFs) based on the selection of the output sample from the multichannel input set is analyzed and optimized. The WVDF output minimizes the sum of weighted angular distances to other input samples from the filtering window. Dependent o ..."
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Cited by 11 (3 self)
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In this paper, a class of Weighted Vector Directional Filters (WVDFs) based on the selection of the output sample from the multichannel input set is analyzed and optimized. The WVDF output minimizes the sum of weighted angular distances to other input samples from the filtering window. Dependent on the weighting coefficients, the class of the WVDFs can be designed to perform a number of smoothing operations with different properties, which can be applied for specific filtering scenarios. In order to adapt the weighting coefficients to varying noise and image statistics, we introduce a methodology, which achieves an optimal tradeoff between smoothing and detail preserving characteristics. The proposed angular optimization algorithms take advantage of adaptive stack filters design and weighted median filtering framework. The optimized WVDFs are able to remove image noise, while maintaining excellent signaldetail preservation capabilities and sufficient robustness for a variety of signal and noise statistics.
An Adaptive Window Mechanism for Image Smoothing
"... Image smoothing using adaptive windows whose shapes, sizes, and orientations vary with image structure is described. Window size is increased with decreasing gradient magnitude, and window shape and orientation are adjusted in such a way as to smooth most in the direction of least gradient. Rather t ..."
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Cited by 3 (0 self)
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Image smoothing using adaptive windows whose shapes, sizes, and orientations vary with image structure is described. Window size is increased with decreasing gradient magnitude, and window shape and orientation are adjusted in such a way as to smooth most in the direction of least gradient. Rather than performing smoothing isotropically, smoothing is performed in preferred orientations to preserve region boundaries while reducing random noise within regions. Also, instead of performing smoothing uniformly, smoothing is performed more in homogeneous areas than in detailed areas. The proposed adaptive window mechanism is tested in the context of median, mean, and Gaussian filtering, and experimental results are presented using synthetic and real images and compared with a stateoftheart method.
On root structures and convergence properties of weighted median filters
 Journal of Circuits, Systems, and Computers
, 1995
"... Abstract. A weighted median filter is a nonlinear digital filter consisting of a window of length 2N + 1 and a weight vector W (WN..... Wo..... WN). A root signal of a median type filter is a signal that is invariant to the filter. However, not all weighted median filters possess the convergence ..."
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Abstract. A weighted median filter is a nonlinear digital filter consisting of a window of length 2N + 1 and a weight vector W (WN..... Wo..... WN). A root signal of a median type filter is a signal that is invariant to the filter. However, not all weighted median filters possess the convergence property. In this paper, we shall study the root structures and the convergence behavior of a subclass of weighted median filters, called class1 filters, which is symmetric in its weight vector. We shall introduce an important parameter, called feature value, and show that any onedimensional unappended signal of length L will converge to a root signal in at most L2 1 3 2(2NW2p) passes of a class1 filter with window width 2N + 1 and the feature value p. 1.
Film and Video Restoration using RankOrder Models
, 1999
"... This thesis introduces the rankorder model and investigates its use in several image restoration problems. More commonly used as filters, the rankorder operators are here employed as predictors. A Laplacian excitation sequence is chosen to complete the model. Images are generated with the model an ..."
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This thesis introduces the rankorder model and investigates its use in several image restoration problems. More commonly used as filters, the rankorder operators are here employed as predictors. A Laplacian excitation sequence is chosen to complete the model. Images are generated with the model and compared with those formed with an AR model. A multidimensional rankorder model is formed from vector medians for use with multidimensional image data. The first application using the rankorder model is an impulsive noise detector. This exploits the notion of `multimodality' in the histogram of a di#erence image of the degraded image and a rankorder filtered version. It uses the EM algorithm and a mixture model to automatically determine thresholds for detecting the impulsive noise. This method compares well with other detection methods, which require manual setting of thresholds, and to stack filtering, which requires an undegraded training sequence. The impulsive noise detector is de...
Threshold Boolean Filtering with Cellular Neural Networks
"... Threshold Boolean Filters (TBF) [1] are used in a broad class of signal and image processing applications, especially in the presence of nonGaussian noise, and in nonlinear feature extraction. In this paper, we give techniques to implement TBFs in the Cellular Neural Network Universal Machine (CNN ..."
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Threshold Boolean Filters (TBF) [1] are used in a broad class of signal and image processing applications, especially in the presence of nonGaussian noise, and in nonlinear feature extraction. In this paper, we give techniques to implement TBFs in the Cellular Neural Network Universal Machine (CNNUM) architecture [2]. In this way, we give a new solution for implementation of TBFs in a general purpose fully parallel architecture, and at the same time obtain a systematic procedure to generate "analogic" programs for the CNNUM. 1 Introduction Threshold Boolean Filters form a wide class of nonlinear filters that includes Stack Filters (SF) [3], Order Statistic (OS) filters [4,5], and morphological filters [6] as special cases. Such filters find application in removal of nonGaussian noise and feature extraction [3,7,8,9], and are therefore used for many purposes in image processing. Architectures for realization of TBFs have been proposed in the literature [1,3,10], generally as seque...
© 2002 Kluwer Academic Publishers. Manufactured in the Netherlands. A New MicroPayment System Using General
"... In recent years electronic commerce has grown rapidly as Internet and web technologies have progressed. Therefore, a secure and efficient payment system for generalpurpose applications is undoubtedly becoming an important issue. Rivest and Shamir have proposed a micropayment scheme which is users ..."
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In recent years electronic commerce has grown rapidly as Internet and web technologies have progressed. Therefore, a secure and efficient payment system for generalpurpose applications is undoubtedly becoming an important issue. Rivest and Shamir have proposed a micropayment scheme which is userspecific and vendorspecific. However, in their scheme, it is required that the user generates a new payword chain for each vendor from which the user makes a purchase. In this paper, we propose a new micropayment system that enables users to make purchases from multiple vendors. Only one payword chain has to be generated which makes this system very efficient. A sequence of payword chains which represents a set of small payments can be authenticated and payment can be made by an efficient method. A lower computation cost and improved system performance is also achieved. Therefore, the new micropayment system has multiple practical applications.
Nonlinear adaptive filter performance in typical applications
 A. Rev. Control
, 1996
"... Abstract: This paper examines approaches to the realisation of nonlinear filters as used in signal and image processing. The design of adaptive nonlinear processors is examined and their application as adaptive equalisers to alleviate bandlimiting, distortion and interference in a typical communicat ..."
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Abstract: This paper examines approaches to the realisation of nonlinear filters as used in signal and image processing. The design of adaptive nonlinear processors is examined and their application as adaptive equalisers to alleviate bandlimiting, distortion and interference in a typical communications channel is investigated. This paper reexamines the equalisation process as one which seeks to correctly classify the channel output into one of a finite and known alphabet of symbols encompassing the data at the channel input. The optimal solution for this classification problem is shown to be inherently nonlinear. Several nonlinear structures are examined, which allow much more complex classification boundaries, and provide greatly enhanced performance for the nonlinear filter over the more conventional linear filter. Finally the use of a nonlinear predictor is investigated for time series analysis.