Showing papers on "Median filter published in 1982"

Median filters: Some modifications and their properties

Abstract: Some modifications of the median filter are given and their properties are derived. In addition, some results for standard median filters are given. It is shown that for nonmedian nth ranked-order operations, repeated application of the operation will reduce any signal to a constant. Also, it is proved that the output of a recursive median filter is invariant to subsequent passes by the same filter.

State description for the root-signal set of median filters

Abstract: Median filtering is a simple digital technique for smoothing signals. One main characteristic of the filter is that it maps the input signal space into a root signal space, where signals invariant to median filters are called roots of the signal. In this paper, we develop the theory for the root signal set of median filters. A tree structure for the root signal set is obtained for binary signals. The number of roots R (n) for a signal of length "n" and window size filter "2s- 1" is exactly represented by the difference equation R(n) = R(n - 1) + R(n - s). A general solution is obtained in a Z domain approach. Finally, a method for faster one dimensional median filter operation is introduced.

Reduction of noise in TV rate electron microscope images by digital filtering

Abstract: SUMMARY Digital framestores can be used to reduce noise in TV rate electron microscope images. Three operating modes: averaging, recursive filtering and Kalman filtering have been investigated. It is shown that there is an optimum choice of filter parameters.

A corner finding algorithm for image analysis and registration

Abstract: In our algorithm the gradient of θ (the gradient direction) in a grey level image is employed for detecting candidates for corner points. Two theorems show that this quantity attains a local maximum at a corner point. Two approaches, median filtering and Hough transform are used effectively to distinguish corner points from noise points. The corner points formed by our algorithm are used in interframe matching.

A generalized comb filtering technique for speech enhancement

Abstract: Because of speech signals nonstationarity, usual comb filtering of noisy speech signals results only in a modest improvement in signal to noise ratio, and only in a small perceptual reduction of structured noise or interference. A generalized comb filtering technique, which applies a time-varying weighting to each pitch period, is mathematically analyzed and shown to be capable of breaking up the noise structure, in addition to comb filtering. This is found to provide a meaningful perceptual improvement when the noise or interference are structured. The mathematical analysis is facilitated by using a polyphase network model of the generalized comb filter. Design constraints and rules are developed and several filter families are proposed. Computer simulation results are discussed.

Real-time ordinal-value filter utilizing reference-function comparison

Abstract: Operating at real-time data rates, the disclosed hardware network generates a signal which closely approximates the Mth-largest of a set of R input data signals. The operational basis of this network is a comparison (121-127) between the input data (101-107) and a monotonically-scanning reference function (110). At that point (140, 150, 160) when the lower (R-M+1) of the inputs have been equaled by an increasing reference, the reference has become the same as the Mth-largest and is used (119b, 165, 170, 175) as the filter output. Analogous operation is achieved with a decreasing reference. When the number R of inputs is odd and M is made equal to ((R+1)/2), the network becomes a real-time median filter.

New Filter Technology in Picture Processing

Abstract: In this paper we describe a new filtering technique for processing video signals called the "LOGICAL FILTER". With the Logical Filter, video signals in the time domain are assumed to be a set of "patterns" and the pattern recognition logic is applied to the filtering of the video signals.

Nonlinear filtering using linear combinations of order statistics

Abstract: In this paper we consider a nonlinear filter whose output is given by a linear combination of the order statistics of the input sequence. Assuming a constant signal in white background noise, the coefficients in the linear combination are chosen to minimize the output MSE for several noise distributions. This new general filter is superior to the well-known median filter, since the median is just a special case.

Digital Pipelined Hardware Median Filter Design For Real-Time Image Processing

Abstract: A hardware median filter is described which is designed to filter imagery at a real-time rate of 10X106 pixels/second. The data is windowed with line buffers, and propagates through n pipe lined stages where n is the number of bits in a pixel. The algorithm described is a form of the radix method of Atamanl modified to reduce the decisionmaking at each stage. Each stage is nearly identical thus making the filter very structured and modular. The filter can be implemented with available logic components and would be useful as a preprocessor in a pattern recognition system.© (1982) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Noise reduction in speech using adaptive filtering I: Signal processing algorithms

Abstract: Adaptive filtering is employed in configurations to filter narrow‐band speech corrupted by noise. These configurations utilize either an independent sample of the input noise or rely on correlation properties of the speech to accomplish cancellation. Necessary constraints on the algorithms to retain and/or improve intelligibility for normal and hearing‐impaired populations are presented. Previous work with the LMS algorithm is compared to the performance resulting from new methods which address the problem created by widespread eigenvalues in the speech plus noise correlation matrix. It is shown that failure to deal with this problem in the single reference application results in a muffling resonant distortion of the speech spectrum. Spectral averages of the original and processed versions of the speech segments are compared to determine improvement. Auditory tests are presented in the companion paper.

A Kalman filter procedure for the processing of the electroencephalogram

Abstract: In the present paper a Kalman filter procedure is illustrated for the reduction of muscular noise superimposed to the electroencephalografic traces (EEG). Such a noise, in fact, has a bandwidth which overlaps the signal carrying the information content useful for the clinical standpoint and, therefore, can not be removed by means of classical digital filtering. A Markov model is used for identifying the signal model (supposed generated by an ARMA process) and the noise model (conceived on the basis of experiments of neurophysiological evidence). The experimental results show a good performance of the filter on the discrete-time EEG signal which is also quantified by the spectral information and the values of the prediction error of the filter itself. Comparison is then carried on with a classical low-pass FIR filter (mostly used in practice) which can not be aggressive enough towards the noise contained in the signal bandwidth but which can undoubtly ameliorate the performance of the Kalman filter.

Noise sensitivity of interpolation and extrapolation matrices.

Abstract: The noise sensitivity of interpolation and extrapolation matrices is investigated. For certain bandwidth and truncation parameters, the interpolation matrix is shown to yield results at a lower noise level than the input data. The input noise level, however, can be lowered by filtering the result. The noise level in the interpolated interval is shown to be lower near where the image is known. The extrapolation matrix is shown to be ill-conditioned, thus demonstrating severe sensitivity to input noise.

Design And Evaluation Of Median Filters For Scintigraphic Image Filtering

Abstract: The problem of reducing image noise and aberrant structures while conserving image sharpness is approached in the context of scintigraphy. Suitably constructed median filters are shown to be superior to conventional smoothing techniques in these applications.© (1982) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

"Optimum" filter for speech enhancement using integrated digital signal processors

Abstract: An algorithm for adaptive filtering of speech in additive acoustic noise is presented In comparison with other speech enhancement algorithms a very low computational cost is required The efficiency of the algorithm is achieved by proper modifications of a Wiener optimum filter with a filter bank Due to the use of digital Lerner band pass filters a very compact filter bank structure is obtained The speech enhancement system has been implemented with INTEL 2920 signal processors As a result, the quality of noisy speech signals band-limited to (300-3300) Hz can be improved for input signal to noise ratios as low as -5dB

Median filter circuit

Abstract: PURPOSE:To extract a median in a short time with a simple hardware, by controlling the replacement between a data stored in a storage means and an input data with an input data comparison means. CONSTITUTION:In extracting the median from n(=7) pieces of input data, n/2+ 1(=4) sets of registers are prepared and input data 9-16 of n/2+1(=4) sets are set in the registers as they are. Data (2-8) inputted next are compared with the maximum value (or minimum value) of the data set in the registers are compared, the data is replaced repetitively and the maximum value 13 (or minimum value) of each register is extracted finally and used as the median.

Image Enhancement Of Chest Radiographs Using Local Statistical Information

Abstract: The use of statistically based image enhancement techniques applied to chest radiographs has been investigated. These techniques include Unsharp Masking, Statistical Differencing and Median Filtering. Their properties are studied and similarities highlighted. In addition, the artefacts produced in the processing are considered, along with techniques for reducing their effects. The application to radiographic images of the chest is described, with consideration of computational requirements.© (1982) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Image Analysis Using Polarized Hough Transform And Edge Enhancer

Abstract: A new image analysis technique is presented in which a modified version of the Hough transform is employed. This transform algorithm operates on edge images in which the polarity of the edge, relative to a reference direction in the image plane, is preserved. The edge polarity is represented by a positive or negative sign resulting from the differentiation operation used in the edge enhancement algorithms. The new Hough transform creates a positive or a negative peak for each edge depending on the polarity of the linear edge features. The polarity information plays a major role in forming or testing a scene hypothesis directly from the Hough transform output. In many applications simple logic performs the equivalent task of several complicated testing procedures. These procedures are normally required after ordinary Hough transformation for the acceptance or rejection of a scene hypothesis. An example is presented in which the objective is to detect a generic river and bridge scene from a range-azimuth image created by an active millimeter wave sensor. In this example, the new Hough transform succeeds in detecting and interpreting the scene, both when it consists of the river and bridge, or the river alone. Also presented as a part of the overall algorithm, are the results of a new edge detection algorithm that employs median filtering prior to edge enhancement, and locally adaptive thresholding in edge detection. Both of these techniques have significantly increased the robustness of the edge detection algorithm, which in turn, has improved the overall performance of the scene analysis algorithm.

Median Filtering of Speckle Noise.

Abstract: : A digital model was developed which simulates the physical process of speckle noise generation in coherent imagery. This was used to determine the effectiveness of two-dimensional digital filters for the reduction of speckle noise. Median filters, ranked order filters, and separable combinations of these were evaluated and found to yield good improvement in image signal-to-noise ratios. (Author)

Evaluation of digital image enhancement techniques for liver scintigrams

Abstract: Digital image enhancement techniques were employed in an effort to improve the resolution of Anger camera liver images. The premise employed was that methods which improve lesion detectability in liver phantoms should also do so in actual liver scintigrams. The types of image processing evaluated were: contrast enhancement, finite and infinite impulse response, modulation transfer function correction, homomorphic and median filtering. Observers were used to evaluate each method for its ability to improve lesion detectability using a five category rating system. The localization receiver operating characteristic (LROC) curve was used as the primary rank ordering method. A point system and analysis of variance were used as corroborative methods, incorporating measures of accuracy and consistency of the observers' answers.

Structured Noise Removal By Using A High Flexible 2D Fir Digital Filter

Abstract: Depending on the adjustment of data acquisition devices, medical images may be degraded by structured noise, which has to be removed before further steps of image processing techniques like contour finding or feature extraction are applied. In the 2D frequency domain of an image, structured noise usually is characterized by a pattern with relatively sharp bounded regions. So, to loose not too much image information by filtering, it is necessary to apply a digital filter, whose bandstop-region has nearly the same pattern as the structured noise region. In this paper, a polynomal approximation algorithm within the scope of the window method of designing 2D Finite-duration Impulse Response (FIR) digital filters is presented, with which it is possible to design lowpass-, highpass-, bandpass-, and bandstop-filters of arbitrary shape, size and position in the 2D frequency domain. The effect of enhancement by this method on a 2D-echocardiogram degraded by ripple structured noise is demonstrated.© (1982) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Noise reduction in images using statistical filtering

Abstract: This paper deals with noise reduction in images using two-dimensional Kalman filtering. To reduce the computational load and the memory storage, updating of state vector is done within a certain distance of the point currently being processed, the support of the filter and dynamical model is restricted to a non-symmetric half plane. Direct histogram specification method is combined with Kalman filtering algorithm. Significant improvement in the quality of the image is obtained. The technique used is particularly attractive for on-line applications. It is also shown that the various gradient computations and template matching schemes work efficiently on estimated image to extract vital features (edges) from the image for the future analysis and studies. The results obtained confirm the feasibility of these algorithms.

Proposal and experimental evaluation of a combined structure "Correlofilter-adapter" for the continuous estimation of a noisy signal with a reference noise

Abstract: We consider the problem of the continuous estimation of an unknown signal S(t) disturbed by an additive noise B 1 (t) when in presence of a reference input consisting only of a noise B 2 (t), correlated with B 1 (t). The signal is independent of the noises. A new structure which combines the correlofilter and the Widrow adaptive filter, is proposed. Experimentally, the system is evaluated and compared to the isolated structures. In the studied cases, the combined structure is shown to be superior to the isolated structures, given equivalent filtering dimensions.

Median filter circuit

Abstract: PURPOSE:To obtain the median of the mask data in a high speed and to realize high efficiency for the processing of pictures, by dividing the density levels of the data on each picture element of the mask for each hierarchical section. CONSTITUTION:A comparison data producing circuit 2 delivers the median of the multivalue level when the signal is first supplied from a decision stage producing circuit 1 and compares the median with the multivalue data. Based on the result of comparison, the next comparison data is delivered from the circuit 2 to be compared successively to obtain the median of the mask data. Thus the median can be obtained in a high speed.

Decomposition and separated adaptive digital processing of degraded images with an visual quality criterion

Abstract: In this paper, image restoration in the context of visual quality criterion and two-component image model is considered. Taking a signal as a two additive components is a very useful way for modeling the two fundamental features of images : edges and textures. We propose a new algorithm which splits the luminance signal of complex images into plateau luminance signal and texture. The method is based on 2-D median filtering with adaptive support shape and offset as estimator of the local-luminance mean value. Using an objective visual quality criterion deduced from a model of human perception, separate adaptive 2-D linear filtering are performed on the two components according to specific action the degradations have made on.

FIR filter for generating multilevel signals from single-bit noise sequences

Abstract: A ROM-based circuit is described for the implementation of finite-impulse-response (FIR) filters used to generate multilevel Gaussian noise signals from pseudorandom binary noise signals. A particular advantage of the circuit is that it can be constructed from readily available, standard components.