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The Schmidt–Kalman (or “consider” Kalman filter) has often been used to account for the uncertainty in so-called “nuisance” parameters when they are impactful to filter accuracy and consistency. Us...

not present; this is a Technical Note, only requiring an Introduction section

A new, efficient switching median–mean filter is proposed to remove high density impulse noise from digital images. The proposed method consists of detection and filtering stages. The pixels that are labeled noise-free in the detection stage remain unchanged and the noisy-pixels are replaced by the reference image based the proposed filter with 3 × 3 window. The simulation results show that the proposed filter outperforms some existing methods, both in vision and quantitative measurements. Moreover, our method is not only efficient to remove high density impulse noise and preserve the details in the image, but also possess a short processing time.

In this paper, we present a solution to the problem of reconstructing the input of a maximally decimated filter bank from the subband components using Wiener filtering. We present a generalized structure for applying Wiener filtering at the output of the analysis stage of a uniform filter bank (UFB). This structure can be used to model a situation where the desired signal is a filtered version of the input signal. Some interesting results for matrix inversion are derived and used to reduce the complexity of the Wiener filter expression. The resulting expression provides many insights into the properties of the Wiener synthesis filter designed. The Wiener synthesis filter turns out to be independent of the input spectral properties. The proposed Wiener synthesis filter bank exploits the pseudocirculant property. Thus all distortions are completely removed and the filter bank reduces to a linear time invariant (LTI) filter of interest. We later extend the analysis to non-uniform filter banks (NUFBs).

We have designed a photoelectric yarn signal acquisition system, which is based on the STM32 processor, having a sample rate up to 270kHz, and uploading data collection through synchronous parallel communication mode; Owing to the large noise of yarn signal and the unobviousness of yarn defect, we respectively adopting wiener filter and mean filter to filter this signal; The simulation result of matlab has manifested that both the wiener filter and mean filter can effectively decrease the noise level of the yarn signal and make the nep defects easier to identify, and that the wiener filter applies to application where the yarn speed is higher , while the mean filter is appropriate to the lower speed spinner.

The main advantage of pseudoquadrature mirror filter cosine modulated filter banks with a spectral factor of a 2Mth band filter is that the optimization stage can be avoided when designing the prototype filter. However, these filter banks are constrained by the condition that the order of the prototype filter has to be an integer multiple of the M-number of channels in the bank. In this paper, we set the conditions that must be imposed to cosine-modulation phase factors so as to cancel the most significant terms of aliasing using a prototype filter of arbitrary length. An example is included to confirm the validity of the theory.

A filter that is recommended to make fast trading. It must then be used only with assets possessing low transaction costs (Forex first).

In this work, a novel way to adjust a bilateral filter is presented. The bilateral filter is a combination of domain and range filtering. The domain filter acts as a low-pass filter. The range filter stands for the nonlinear component and plays an important part in edge preserving. Both filtering components can be adjusted by according parameters. Pursuant to our experience and achieved results in terms of the image quality it is more effective to readjust the range filter to the noise level than to cope with the fine tuning of the spatial filter. In this work, we show how the adjustment parameter for the nonlinear range component can be derived from the standard deviation of noise, which allows automatic noise-adaptive adjustment of the filter.

In this paper, the theory of uniform filter banks using all-pass tilters is further developed. A new structure of two stage filter banks using all-pass filter is proposed. The prestage is half-band filter with period, the post-stage is two sets of band-pass filter banks. The pre-stage filter stop-band just controls the don’t-care-band of the post-stage filter banks using all-pass polyphase, so as to realize a continuous stop-band property. Moreover, a method of synthesizing filter bank is derived, which eliminates aliasing and amplitude distortions of the analysis/synthesis system. Finally, an example is given.

WOS: 000254240200009, A flexible synthesis procedure for electronically tunable nth-order current-mode (CM) universal filter using state variable-method is given. The proposed configuration uses n+1 multi-output second generation current conveyors (MO-CCIIs), n capacitors and n resistors. These resistors can be removed by using multi-output second generation current controlled conveyors (MO-CCCIIs) instead of MO-CCIIs. It is straightforward to find the values of the passive elements from the coefficients of the transfer function to be realized. The validity of the proposed filter is verified through PSpice simulations.

By using a bit vector and a set of hash functions to represent data set, bloom filter can query a given data effectively. Bloom filter can be used to determine an element belongs to data set or not. Split bloom filter is amelioration to the bloom filter, which use a S times N bit matrix to represent data set. In distributed systems, if the number of the elements increases continually, the increasing error rate of bloom filter will make the representation nonsensically. Split bloom filter can only weaken this problem. In this paper, a new kind of bloom filter, named as K-divided bloom filter, is presented. Compared with split bloom filter, it can reduce space and time spending and has a resembling or better performance. K-divided bloom filter gets better tradeoff among error rate, space and time.

This paper proposes the new two-pole band-pass filter design principle for the all-pass filter and notch filter by applying the least square. The first step is to design notch filter by using pole-zero placement and then modify pole positions to control pass-band filter gain to ensure the symmetry with the maximum gain at the target level. After that, there is the design of all-pass filter with pole at the same positions as the notch filters to make the negative cascade with the designed notch filter to get the transfer function with band-pass filter magnitude response. The results from the experiments on MATLAB have shown the two-pole band-pass filter of the new design with the accurate and symmetric gain

A new filter is proposed based on the filter created by Dr. Salvador Bosso (1994) in Chile. This filter, called the Bosso's filter, has an interesting behavior that depends on its parameters. Some results for different values of its parameters /spl lambda/ and a, characterizing the filter of Bosso, are presented. When the discrete equation is obtained, a third parameter N appears. This parameter corresponds to the number of pixels in the kernel. To analyze the behavior of the filter, IDL software is used on the bidimensional simple images.

The responses of reverse jacket (RJ) filter banks are simulated in Matlab. The FIR filter with 128 taps is used as a basic filter and decimation factor is computed for RJ matrices. The input image, Lena, is processed with RJ filter banks at N=2, 3, 5, 6, 8. We identify good quality performances with low decimation factor. The error is discussed.

A new class of morphological filters is proposed for smoothing an image contaminated with noise. A multiple model that includes the combination of linear and nonlinear operations is used in the design of the new filter. The performance of the averaging version of this new filter is similar to that of the alpha-trimmed mean filter. The structure-preserving properties of this new filter depend on the values assigned to the coefficients in the filter. The idempotent property is obtained when a closing-min and opening-max version of the filter is used. The root structure of the output signal is also investigated. >

A new edge-preserving filter which is called the modified multilevel FIR median hybrid (FMH) filter for image smoothing is reported. Subfilters of this filter combine the mean filter with an FMH filter. The performance of the subfilter is almost equal in edge preserving property and superior in noise smoothing ability to conventional subfilters. Experimental results indicate good performance. >

This paper describes a new method for the design of subband filters based on nonuniform filter banks. We use two-dimensional (2-D) filter and fix one axis to arbitrary frequency in 2-D plane. Then frequency response of it turn out a cross section of 2-D filter. Using 2-D filter with power complementary, we obtain subband filters and rational sampling filters corresponding to division ratio easily. As a result, the system is realized with a few filter design.

In this paper, IIR digital filter design based on the frequency-response masking approach is presented. The overall filter structure is based on the periodic model filter, complementary periodic model filter, and masking filters. The periodic model filter is obtained by replacing each delay in the prototype low-pass IIR filter by M delays. Masking filters are designed to eliminate unwanted bands from the periodic model filter or complementary periodic model filter. The transition bandwidth of the overall filter is M times smaller to that of the prototype filter. This technique can be used to design sharp low-pass, high-pass, band-pass, and band-stop filters. IIR model filters are implemented as low-sensitivity wave lattice digital filters (WDF-s) consisting of two all-pass branches in parallel. In all-pass sections, each delay is replaced with M delays to obtain periodic model filter. This way maximal sample frequency of the filter is M times increased. We show that the transfer function of the model filter is an elliptic minimal Q factors (EMQF) filter suitable for the efficient WDF implementation.

We study the optimum (in the minimum mean-square error sense) linear periodically time-varying deconvolution filter of finite size. We show that the filter can be in the form of lapped transform or multirate filter-bank, and it includes the FIR Wiener filter as a special case. We demonstrate that the proposed filter always possesses a gain over the Wiener filter.

In this paper, an hybrid filter is presented for restoration of color images in a mixed noise environment, where both impulsive and correlation noise may be present. The proposed hybrid filter is composed of two stages, the first stage to remove the impulsive noise and the second to remove the correlated noise. The median filters and their variants are the most popular filter types used for impulsive noise suppression. However, median filters and their variants tend to remove fine image details and destroy fine texture in the mixed noise environment or when the signal to noise ratio is low. In order to overcome the limitations of the median filters, an adaptive simplified-model Kalman filter (ASMKF) is propsed for the suppression of impulsive noise in the first stage of the hybrid filter. In the second stage of the proposed hybrid filter, to remove correlated noise, discrete Wavelet Transform (DWT) filter is applied on the impulsive-noise-free image obtained from the first stage. The efficacy of the proposed hybrid filter is illustrated through implementation results obtained on the restoration of a color image.

A new directional filter bank for image analysis and classification is proposed. This paper introduces an improved structure in order to visualize subband outputs of the directional filter banks, while retaining the attractive properties of the original directional filter banks such as 1-D separable filtering, perfect reconstruction, and maximal decimation. Using this structure, any arbitrary 2/sup n/ band directional filter bank can be implemented by cascading simple directional filter bank blocks, unlike the original structure that needs a parallel structure for visualizing subband outputs. Also, in order to have nondistorted phase information in the subbands for visualization, both FIR and IIR filter prototypes that can be implemented efficiently are provided for linear phase filtering. This paper shows the approach proposed here can be applied to image analysis and classification.

Smooth surfaces are approximated by polyhedral surfaces for a number of computational purposes. An inherent problem of these approximation algorithms is that the resulting polyhedral surfaces appear faceted. Within a recently introduced signal processing approach to solving this problem [7, 8], surface smoothing corresponds to low-pass filtering. In this paper we look at the filter design problem in more detail. We analyze the stability properties of the low-pass filter described in [7, 8], and show how to minimize its running time. We show that most classical techniques used to design finite impulse response (FIR) digital filters can also be used to design significantly faster surface smoothing filters. Finally, we describe an algorithm to estimate the power spectrum of a signal, and use it to evaluate the performance of the different filter design techniques described in the paper.

The construction of filters or filter operators is an important problem in image processing. In this paper it is described how one can construct a filter operator based on the Distance Transformation for grey-scale image. This operator is similar to max/min filters for grey-scale images. We call this operator quasi-median filter. It is not a filter from the morphological point of view like median filter, but it posses filter (mean) properties.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

An algorithm to choose which pixels to zero out in an otherwise phase-only filter is presented. This algorithm involves a simple thresholding technique applied to the general spatial filter described in previous work. Having fixed those pixels which are to be set equal to 0 in the filter, one can then view the remaining phases as free parameters and design a good 0 and continuous phase filter by optimizing the filter's signal-to-clutter ratio using the author's techniques. One can the discretize this zero and phase filter into one whose entries are 0 or one of the nth roots of unity. For example, ternary (0, +1, and -1) filter are of this form as are filters whose entries are 0 and the sixteenth roots of unity. Examples of such are given. This paper together with its ancestor provides a completely automatic way to start with a training set of true and false targets of any size and automatically and without human intervention produce optimized filters for use in extant spatial light modulators.

The fractional correlation is a new operation that can easily be implemented by optical means. This operation might be useful for shift-variant pattern recognition and for image restoration. The Wiener filter is the optimal filter according to the minimal square-error criterion. For a given spectral noise that distorts the reference image, this filter is optimal for restoring an image in noise. A fractional Wiener filter is suggested for restoring reference objects in a fractional correlation system. The new filter sometimes performs better than the conventional Wiener filter.

A novel type of filter is suggested for digital communication Systems. This filter response is similar to an ideal raised-cosine filter, and significantly better than classical Butterworth filters, concerning intersymbol interference. The new filter is realised using a simple active filter.

Analysis by synthesis calculates a difference by subtracting (130) synthesized speech from input speech. The synthesized speech is formed by exciting long and short term filters (124,126) with excitation vectors from a codebook store (114) which is searched by codebook generation (120). A weighting filter (132) is applied to the difference signal and the weighted difference is used to calculate an energy measure (134) which is used to control the codebook search (140). The weighting filter is an Rth-order filter controlled with calculated coefficients. The method for calculating coefficients models the frequency response of L Pth-order filters by a single Rth-order filter, where the order R ~ LxP. This method increases the control of a speech coder filter without an increase in hardware complexity.

We define a filter on [ λ ] κ {\left [ \lambda \right ]^\kappa } with properties similar to those of the closed unbounded filter in P κ ( λ ) {P_\kappa }\left ( \lambda \right ) . This filter’s behaviour depends on set theoretical hypotheses.

In this paper a new general second-order digital filter section is proposed. One of the two quantizers used in the filter applies controlled rounding which has the effect that limit cycles are completely eliminated under constant-input conditions. Furthermore, the configuration of the filter is such that multipliers can be saved in case the filter is used as an all-pass filter or as a filter with zeros of transmission on the unit circle in the z domain.

This paper deals with the problem of finding a Wiener filter when the length of the filter output in not larger than the length of the filter input. Measure for the efficiency of a filter is defined in terms of the relation between the desired filter output and the actual filter output. This measure, called the filter efficiency, is used to find the optimum length of the filter memory function. The relation between the signal-to-noise-ratio (SNR) of the filter input and the SNR of the filter output is discussed. It is shown that there is always some improvement in the SNR through the use of a Wiener filter.

Equation (3.1 or 3) mathematically describes the dynamic model in the Kalman-Bucy filter, whose output is a stochastic vector process to be estimated on the basis of noise-contaminated observations. To complete the Kalman-Bucy model for the estimation problem, we now define the observation process.

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