alpha trimmed means and their relationship to median filters suppose that x is a finite set of n numbers the trimmed mean of x is obtained by sorting x into ascending order removing trimming a fixed fraction alpha 0 leq alpha leq 0 5 from the high and low ends of the sorted set and computing the average of the remaining values when applied to a sliding window of length lw the trimming process is called trim filtering for 0 5 the trimmed mean of a set is the median of the set and the filtering operation is called median filtering repeated application of a median filter to the output of a previous median filter of the same length lw eventually produces a signal which is invariant to median filtering this final signal is called the root signal this paper explains the relationship between trimmed means and median filters derives a simple straightforward and fast algorithm for applying a median filter and provides a new explanation of the convergence of repeated median filtering to the root signal the latter result incorporates an approach which permits generalization of the associated concepts to a larger class of index map filters

waveform relaxation for reaction diffusion equations abstract we report a new waveform relaxation wr algorithm for general semi linear reaction diffusion equations the superlinear rate of convergence of the new wr algorithm is proved and we also show the advantages of the new approach superior to the classical wr algorithms by the estimation on iteration errors the corresponding discrete wr algorithm for reaction diffusion equations is presented and further the parallelism of the discrete wr algorithm is analyzed moreover the new approach is extended to handle the coupled reaction diffusion equations numerical experiments are carried out to verify the effectiveness of the theoretic work

a multidimensional nonlinear edge preserving filter for magnetic resonance image restoration the paper presents a multidimensional nonlinear edge preserving filter for restoration and enhancement of magnetic resonance images mri the filter uses both interframe parametric or temporal and intraframe spatial information to filter the additive noise from an mri scene sequence it combines the approximate maximum likelihood equivalently least squares estimate of the interframe pixels using mri signal models with a trimmed spatial smoothing algorithm using a euclidean distance discriminator to preserve partial volume and edge information partial volume information is generated from voxels containing a mixture of different tissues since the filter s structure is parallel its implementation on a parallel processing computer is straightforward details of the filter implementation for a sequence of four multiple spin echo images is explained and the effects of filter parameters neighborhood size and threshold value on the computation time and performance of the filter is discussed the filter is applied to mri simulation and brain studies serving as a preprocessing procedure for the eigenimage filter the eigenimage filter generates a composite image in which a feature of interest is segmented from the surrounding interfering features it outperforms conventional pre and post processing filters including spatial smoothing low pass filtering with a gaussian kernel median filtering and combined vector median with average filtering

an interface capturing method with a continuous function the thinc method with multi dimensional reconstruction an interface capturing method with a continuous function is proposed within the framework of the volume of fluid vof method being different from the traditional vof methods that require a geometrical reconstruction and identify the interface by a discontinuous heaviside function the present method makes use of the hyperbolic tangent function known as one of the sigmoid type functions in the tangent of hyperbola interface capturing thinc method f xiao y honma k kono a simple algebraic interface capturing scheme using hyperbolic tangent function int j numer methods fluids 48 2005 1023 1040 to retrieve the interface in an algebraic way from the volume fraction data of multi component materials instead of the 1d reconstruction in the original thinc method a multi dimensional hyperbolic tangent function is employed in the present new approach the present scheme resolves moving interface with geometric faithfulness and compact thickness and has at least the following advantages 1 the geometric reconstruction is not required in constructing piecewise approximate functions 2 besides a piecewise linear interface curved quadratic surface can be easily constructed as well and 3 the continuous multi dimensional hyperbolic tangent function allows the direct calculations of derivatives and normal vectors numerical benchmark tests including transport of moving interface and incompressible interfacial flows are presented to validate the numerical accuracy for interface capturing and to show the capability for practical problems such as a stationary circular droplet a drop oscillation a shear induced drop deformation and a rising bubble

a fuzzy operator for the enhancement of blurred and noisy images rule based fuzzy operators are a novel class of operators specifically designed in order to apply the principles of approximate reasoning to digital image processing this paper shows how a fuzzy operator that is able to perform detail sharpening but is insensitive to noise can be designed the results obtainable by the proposed technique in the enhancement of a real image are presented

short note analytical and geometrical tools for 3d volume of fluid methods in general grids it is well known that volume of fluid vof methods in three dimensions especially those based on unsplit advection schemes involve highly complex geometrical operations the objective of this work is to propose for general grids and three dimensional cartesian geometry simple and efficient geometrical tools for volume truncation operations that typically arise in vof methods and an analytical method for local volume enforcement the results obtained for different tests and grid types show that the proposed analytical method may be as much as three times faster than brent s iterative method advection tests were carried out using hexahedral grids obtained from deformation of a cubic grid to assess the accuracy of the proposed tools in combination with a recently proposed unsplit plic vof method

a direct time integral thinc scheme for sharp interfaces abstract this paper describes an improved multi dimensional tangent of hyperbola interface capturing thinc scheme that uses a direct time integration of the hyperbolic tangent function the new time integral thinc scheme is based on the assumption that the interface remains unchanged and moves with the velocity of the cell center during a computational time step a time varying hyperbolic tangent function representing the two phase distribution is then constructed and directly integrated in time compared with existing thinc methods that generally use third order total variation diminishing runge kutta rk3 schemes to update the volume fraction the proposed method requires only one reconstruction step thus reducing the computational cost several classical advection tests have been implemented and the results indicate that the proposed direct time integral thinc method 1 achieves computational errors close to those of the rk3 scheme at a computational cost that is close to that of the first order explicit scheme and 2 preserves better boundedness of the volume fractions than the original rk3 based thinc methods when using a larger steepness parameter and higher courant numbers the proposed approach is employed with the incompressible navier stokes equations to solve a 2d dambreak problem and the numerical results agree well with the corresponding experimental data demonstrating the applicability of the direct time integral thinc method

design and performance of combination filters for signal restoration a class of nonlinear moving window filters is investigated for restoration and detection of signals embedded in additive white gaussian and non gaussian noise the filters of this class called combination filters c filters use both rank order and temporal order information from the input observation sequence within finite processing windows to produce the outputs a c filter combines the characteristics of linear fir finite impulse response filters and nonlinear filters of the order statistics type the output of a c filter in each processing window is defined to be the rank order dependent weighting of temporal order data both analytical and training procedures for designing the c filters are considered to get further improvement in overall performance the authors extend the concept of c filters and introduce a class of generalized c filters gc filters which are shown to have desirable properties performance characteristics of c and gc filters in signal restoration are considered through computer simulation

adaptive trimmed mean filters for image restoration an adaptive smoothing filter is proposed for reducing noise in digital signals of any dimensionality the adaptive procedure is based on the selection of an appropriate inner or outer trimmed mean filter according to local measurements of the tail behavior impulsivity of the noise process the set of trimmed means used provides robustness against a wide range of noise possibilities ranging from very shallow tailed to very heavy tailed a monte carlo analysis using a family of generalized exponential distributions supports the choice of the trimmed mean selected for measured values of an impulsivity statistic the assumption underlying the definition of the filter is that the signal to be filtered is locally smoothly varying and that the noise process is uncorrelated and derives from an unknown unimodal symmetric distribution for image processing applications a second statistic is used to mark the location of abrupt intensity changes or edges in the vicinity of an edge the trend preserving median filter is used since the impulsivity and edge statistics used in defining the adaptive filter are both functions of order statistics the extra computation required for their calculation is minimal examples are provided of the filter as applied to images corrupted by a variety of noises

efficient implementation of thinc scheme in this paper we improve the multi dimensional thinc tangent of hyperbola for interface capturing scheme f xiao y honma t kono a simple algebraic interface capturing scheme using hyperbolic tangent function int j numer meth fluid 48 2005 1023 the thinc scheme is a vof volume of fluid type method in the original thinc scheme one dimensional thinc scheme was straightforwardly used for multi dimensional cases in this paper we propose the wlic weighed line interface calculation method to extend the thinc scheme to multi dimension in the wlic method the interface is reconstructed by taking an average of line interfaces along x y and z coordinates with the weights calculated from surface normal the wlic method can extend the thinc scheme to multi dimension while maintaining simplicity of implementation and achieve a higher accuracy than the original thinc scheme the wlic method can readily extend the thinc scheme to three dimension

flair fluz line segment model for advection and interface reconstruction abstract a computational technique for solving fluid problems with free surfaces and interfaces is presented the conventional cell volume fraction approach is employed for tracking the interfaces however for surface advection and its reconstruction a new and more accurate flair flux line segment model for advection and interface reconstruction algorithm is developed the surface is approximated by a set of line segments fitted at the boundary of every two neighboring computational cells a criterion is developed for identifying the line segment orientation by inspecting the cell volume fractions the new cell volume fraction field is obtained by integrating the advected area underneath the interface line segment as an example this technique is applied to the capillary driven viscous flow of an initially elliptic two dimensional fluid zone the problem is posed mathematically as a solution of the navier stokes equations with moving free surface boundary conditions the damping motion of the fluid zone is observed through transport of the free surface which is related to the instantaneous internal velocity field under the influence of surface tension and viscous forces

a theoretical analysis of the properties of median filters necessary and sufficient conditions for a signal to be invariant under a specific form of median filtering are derived these conditions state that a signal must be locally monotone to pass through a median filter unchanged it is proven that the form of successive median filtering of a signal i e the filtered output is itself again filtered eventually reduces the original signal to an invariant signal called a root signal for a signal of length l samples a maximum of frac 1 2 l 2 repeated filterings produces a root signal

stack filters the median and other rank order operators possess two properties called the threshold decomposition and the stacking properties the first is a limited superposition property which leads to a new architecture for these filters the second is an ordering property which allows an efficient vlsi implementation of the threshold decomposition architecture motivated by the success of rank order filters in a wide variety of applications and by the ease with which they can now be implemented we consider in this paper a new class of filters called stack filters they share the threshold decomposition and stacking properties of rank order filters but are otherwise unconstrained they are shown to form a very large class of easily implemented nonlinear filters which includes the rank order operators as well as all compositions of morphological operators the convergence properties of these filters are investigated using techniques similar to those used to determine root signal behavior of median filters the results obtained include necessary conditions for a stack filter to preserve monotone regions or edges in signals the output distribution for these filters is also found all the stack filters of window width 3 are determined along with their convergence properties among these filters are found two which we have named asymmetric median filters they share all the properties of median filters except that they remove impulses of one sign only that is one removes only positive going edges the other removes only negative going edges while the median filter removes impulses of both signs this investigation of the properties of stack filters thus produces several new useful and easily implemented filters

adaptive alpha trimmed mean filters under deviations from assumed noise model alpha trimmed mean filters are widely used for the restoration of signals and images corrupted by additive non gaussian noise they are especially preferred if the underlying noise deviates from gaussian with the impulsive noise components the key design issue of these filters is to select its only parameter spl alpha optimally for a given noise type in image restoration adaptive filters utilize the flexibility of selecting spl alpha according to some local noise statistics in the present paper we first review the existing adaptive alpha trimmed mean filter schemes we then analyze the performance of these filters when the underlying noise distribution deviates from the gaussian and does not satisfy the assumptions such as symmetry specifically the clipping effect and the mixed noise cases are analyzed we also present a new adaptive alpha trimmed filter implementation that detects the nonsymmetry points locally and applies alpha trimmed mean filter that trims out the outlier pixels such as edges or impulsive noise according to this local decision comparisons of the speed and filtering performances under deviations from symmetry and gaussian assumptions show that the proposed filter is a very good alternative to the existing schemes

toward efficient and accurate interface capturing on arbitrary hybrid unstructured grids the thinc method with quadratic surface representation and gaussian quadrature abstract a novel interface capturing scheme is proposed to compute moving interface on arbitrary hybrid unstructured grids different from conventional volume of fluid vof schemes that require complicated geometric manipulations for interface reconstructions the present method can be viewed as a hybrid geometric algebraic type vof approach i e the interface is implictly retrieved from an algebraic function that effectively makes use of the geometrical information such as normal direction and curvature of the interface unlike previous versions of the thinc tangent of hyperbola interface capturing method the interface is represented by a quadratic surface for grid cells of arbitrary shapes in this scheme the gaussian quadrature is used to estimate the integration of the cell wise multi dimensional hyperbolic tangent reconstruction function which is then used to retrieve the interface from the volume fraction value of the target cell the gaussian quadrature is also used to compute the numerical fluxes from the reconstruction function numerical accuracy for reconstruction and flux computation can be effectively improved by increasing quadrature points the whole solution procedure follows the finite volume method for advection transport and is thus simple and easy to use for cells of arbitrary shapes as verified in the benchmark tests in this paper the presented scheme so called thinc qq thinc method with quadratic surface representation and gaussian quadrature scheme shows significantly improved geometrical fidelity of interface representation particularly for curved surface despite algorithmic simplicity the solution quality of thinc qq is comparable to other existing vof methods with plic geometrical interface reconstructions and thus an accurate and efficient vof scheme of great practical significance for unstructured grids

short note revisit to the thinc scheme a simple algebraic vof algorithm this short note presents an improved multi dimensional algebraic vof method to capture moving interfaces the interface jump in the thinc tangent of hyperbola for interface capturing scheme is adaptively scaled to a proper thickness according to the interface orientation the numerical accuracy in computing multi dimensional moving interfaces is significantly improved without any geometrical reconstruction the proposed method is extremely simple and easy to use and its numerical accuracy is superior to other existing methods of its kind and comparable to the conventional plic piecewise linear interface calculation type vof schemes

edge detectors based on nonlinear filters a class of edge detectors is proposed which is obtained from the difference of the outputs of two nonlinear filters the nonlinear filters used are based on nonlinear means which contain homomorphic filters or order statistic which contain median filters the performance of these edge detectors in the presence of noise is evaluated and is compared to the performance of well established edge detectors their computational requirements are described and some examples are presented

reconstructing volume tracking a new algorithm for the volume tracking of interfaces in two dimensions is presented the algorithm is based upon a well defined second order geometric solution of a volume evolution equation the method utilizes local discrete material volume and velocity data to track interfaces of arbitrarily complex topology a linearity preserving piecewise linear interface geometry approximation ensures that solutions generated retain second order spatial accuracy second order temporal accuracy is achieved by virtue of a multidimensional unsplit time integration scheme we detail our geometrically based solution method in which material volume fluxes are computed systematically with a set of simple geometric tasks we then interrogate the method by testing its ability to track interfaces through large controlled topology changes whereby an initially simple interface configuration is subjected to vortical flows numerical results for these strenuous test problems provide evidence for the algorithm s improved solution quality and accuracy

iterative truncated arithmetic mean filter and its properties the arithmetic mean and the order statistical median are two fundamental operations in signal and image processing they have their own merits and limitations in noise attenuation and image structure preservation this paper proposes an iterative algorithm that truncates the extreme values of samples in the filter window to a dynamic threshold the resulting nonlinear filter shows some merits of both the fundamental operations some dynamic truncation thresholds are proposed that guarantee the filter output starting from the mean to approach the median of the input samples as a by product this paper unveils some statistics of a finite data set as the upper bounds of the deviation of the median from the mean some stopping criteria are suggested to facilitate edge preservation and noise attenuation for both the long and short tailed distributions although the proposed iterative truncated mean itm algorithm is not aimed at the median it offers a way to estimate the median by simple arithmetic computing some properties of the itm filters are analyzed and experimentally verified on synthetic data and real images

a generalization of median filtering using linear combinations of order statistics we consider a class of nonlinear filters whose output is given by a linear combination of the order statistics of the input sequence assuming a constant signal in white noise the coefficients in the linear combination are chosen to minimize the output mse for several noise distributions it is shown that the optimal order statistic filter osf tends toward the median filter as the noise becomes more impulsive the optimal osf is applied to an actual noisy image and is shown to perform well combining properties of both the averaging and median filters a more general design scheme for applications involving nonconstant signals is also given

volume of fluid interface tracking with smoothed surface stress methods for three dimensional flows motivated by the need for three dimensional methods for interface calculations that can deal with topology changes we describe a numerical scheme built from a volume of fluid interface tracking technique that uses a piecewise linear interface calculation in each cell momentum balance is computed using explicit finite volume finite differences on a regular cubic grid surface tension is implemented by the continuous surface stress or continuous surface force method examples and verifications of the method are given by comparing simulations to analytical results and experiments for sedimenting droplet arrays and capillary waves at finite reynolds number in the case of a pinching pendant drop both three dimensional and axisymmetric simulations are compared to experiments agreement is found both before and after the reconnections

a new volume conservation enforcement method for plic reconstruction in general convex grids a comprehensive study is made of methods for resolving the volume conservation enforcement problem in the plic reconstruction of an interface in general 3d convex grids different procedures to bracket the solution when solving the problem using previous standard methods are analyzed in detail a new interpolation bracketing procedure and an improved analytical method to find the interface plane constant are proposed these techniques are combined in a new method to enforce volume conservation which does not require the sequential polyhedra truncation operations typically used in standard methods the new methods have been implemented into existing geometrical routines described in lopez and hernandez 15 which are further improved by using more efficient formulae to compute areas and volumes of general convex 2 and 3d polytopes different tests using regular and irregular cell geometries are carried out to demonstrate the robustness and substantial improvement in computational efficiency of the proposed techniques which increase the computation speed of the mentioned routines by up to 3 times for the 3d problems considered in this work

a structure for adaptive order statistics filtering in applications such as smoothing and enhancement of images adaptive filtering techniques offer the flexibility needed for good performance with non stationary observations many adaptive schemes can be based on the idea of determining the local statistics of the signal through appropriate tests on the data to aid in the selection of a filtering procedure that is suited to the data in the paper the authors consider decision directed or data dependent adaptive filtering schemes that are based on order statistics a general formulation for such a class of adaptive order statistics filters is presented approximate statistical performance analysis especially in the presence of edges may be carried out for this entire class of filters the authors give examples of some existing filters that fit into this framework the formulation also accommodates filters that employ multiple windows in their operation to illustrate the potential of this class of multiple window mw filters they construct and analyze simple filters like the triple window median tw med and the triple window median of means tw mom filters that are shown to yield useful performance the class of mean median hybrid mmh filters is also presented as a simple example which may be extended to give interesting performance

short note an interface capturing method with a continuous function the thinc method on unstructured triangular and tetrahedral meshes a novel interface capturing method is proposed to compute moving interfaces on unstructured grids with triangular 2d and tetrahedral 3d elements different from the conventional vof volume of fluid method which involves geometric reconstructions of the interface the present method is based on the algebraic reconstruction approach originally developed in the thinc tangent of hyperbola interface capturing scheme by xiao et al 2005 17 a continuous multidimensional hyperbolic tangent function is employed for retrieving the jump like distribution of the indicator function which avoids the explicit geometric representation of the interface and thus substantially reduces the algorithmic complexity in unstructured grids numerical diffusion and smearing are effectively eliminated and the compact thickness of the jump transition layer in the volume fraction is retained throughout the computation even for largely deformed interface the solution quality of the present scheme is comparable to the vof method with plic piecewise linear interface calculation algorithm

analytical relations connecting linear interfaces and volume fractions in rectangular grids abstract the computational geometric problems arising when a linear interface cuts a cube are considered they are of interest in particular for the calculation of volume fractions or interface positions in three dimensional interface calculations in the volume of fluid vof methods typically the normal vector is known one then wants to compute the volume fraction knowing the interface position or conversely the interface position knowing the volume fraction explicit expressions of general use are given and the algorithms used to search for solutions are described in detail explicit formulas for cubic roots are found to be less than two thirds as time consuming as newton raphson iterations

a new algorithm for image noise reduction using mathematical morphology morphological openings and closings are useful for the smoothing of gray scale images however their use for image noise reduction is limited by their tendency to remove important thin features from an image along with the noise the paper presents a description and analysis of a new morphological image cleaning algorithm mic that preserves thin features while removing noise mic is useful for gray scale images corrupted by dense low amplitude random or patterned noise such noise is typical of scanned or still video images mic differs from previous morphological noise filters in that it manipulates residual images the differences between the original image and morphologically smoothed versions it calculates residuals on a number of different scales via a morphological size distribution it discards regions in the various residuals that it judges to contain noise mic creates a cleaned image by recombining the processed residual images with a smoothed version the paper describes the mic algorithm in detail discusses the effects of parametric variations presents the results of a noise analysis and shows a number of examples of its use including the removal of scanner noise it also demonstrates that mic significantly improves the jpeg compression of a gray scale image

lum filters a class of rank order based filters for smoothing and sharpening a new class of rank order based filters called lower upper middle lum filters is introduced the output of these filters is determined by comparing a lower and an upper order statistic to the middle sample in the filter window these filters can be designed for smoothing and sharpening or outlier rejection the level of smoothing done by the filter can range from no smoothing to that of the median filter this flexibility allows the lum filter to be designed to best balance the tradeoffs between noise smoothing and signal detail preservation lum filters for enhancing edge gradients can be designed to be insensitive to low levels of additive noise and to remove impulsive noise furthermore lum filters do not cause overshoot or undershoot some statistical and deterministic properties of the lum filters are developed and a number of experimental results are presented to illustrate the performance these experiments include applications to 1d signals and to images

theory of order statistic filters and their relationship to linear fir filters necessary and or sufficient conditions on both the filter coefficients and the signal process are derived in order that nonrecursive order statistic os and linear filtering are equivalent operations the results indicate that an understanding of os filters hinges on a better understanding of the properties of signals containing logically monotonic components the results extend a number of previous theories characterizing the well known median and ranked order filters to a broader class of filters and input signals

estimation from quantized gaussian measurements when and how to use dither subtractive dither is a powerful method for removing the signal dependence of quantization noise for coarsely quantized signals however estimation from dithered measurements often naively applies the sample mean or midrange even when the total noise is not well described with a gaussian or uniform distribution we show that the generalized gaussian distribution approximately describes subtractively dithered quantized samples of a gaussian signal furthermore a generalized gaussian fit leads to simple estimators based on order statistics that match the performance of more complicated maximum likelihood estimators requiring iterative solvers the order statistics based estimators outperform both the sample mean and midrange for nontrivial sums of gaussian and uniform noise additional analysis of the generalized gaussian approximation yields rules of thumb for determining when and how to apply dither to quantized measurements specifically we find subtractive dither to be beneficial when the ratio between the gaussian standard deviation and quantization interval length is roughly less than one third when that ratio is also greater than 0 822 k text 0 930 for the number of measurements k text 20 estimators we present are more efficient than the midrange

streaking in median filtered images this paper presents a probabilistic analysis of the streaking or blotching effect commonly observed in median filtered signals in both one and two dimensions the effcts are identified as runs of equal or nearly equal values which create visual impressions that have no visual correlate for one dimensional discrete iid random signals with continuous input probability densities the probability of a streak of length l occurring is computed and shown to be independent of the input probability distribution expressions for the first and second moments of the streak length are also derived and certain asymptotic results are given as the analysis and definition of the analogous effect in two dimensions is less tractable the probability that medians taken from distinct overlapping windows will take the same value is derived for various filter geometries the analytic results are supported by examples using both one and two dimensional signals

a class of order statistic lms algorithms conventional gradient based adaptive filters as typified by the well known lms algorithm use an instantaneous estimate of the error surface gradient to update the filter coefficients such a strategy leaves the algorithm extremely vulnerable to impulsive interference a class of adaptive algorithms employing order statistic filtering of the sampled gradient estimates is presented these algorithms dubbed order statistic least mean squares oslms are designed to facilitate adaptive filter performance close to the least squares optimum across a wide range of input environments from gaussian to highly impulsive three specific oslms filters are defined the median lms the average lms and the trimmed mean lms the properties of these algorithms are investigated and the potential for improvement demonstrated finally a general adaptive oslms scheme in which the nature of the order statistic operator is also adapted in response to the statistics of the input signal is presented it is shown that this can facilitate performance gains over a wide range of input data types

combination median filter a detail and structure preserving smoothing filter is introduced it is called the combination median filter as it uses directional median multilevel median and median filters to smooth different regions of the image the decision about the region is made by robust dixon s r test which is well known in statistics for outlier detection the threshold value of dixon s test can be kept constant as a result the filtering algorithm operates like a quasi nonadaptive filter and no computation of local statistics is involved some properties of the filter as well as detailed experimental results that demonstrate its superior performance are presented

a robust approach to image enhancement based on fuzzy logic in this paper we propose a robust approach to image enhancement based on fuzzy logic that addresses the seemingly conflicting goals of image enhancement i removing impulse noise ii smoothing out nonimpulse noise and iii enhancing or preserving edges and certain other salient structures we derive three different filters for each of the above three tasks using the weighted or fuzzy least squares ls method and define the criteria for selecting each of the three filters the criteria are based on the local context and they constitute the antecedent clauses of the fuzzy rules the overall result of the fuzzy rule based system is the combination of the results of the individual filters where each result contributes to the degree that the corresponding antecedent clause is satisfied this approach gives us a powerful and flexible image enhancement paradigm results of the proposed method on several types of images are compared with those of other standard techniques

noise reduction of image sequences using motion compensation and signal decomposition in this paper a new spatio temporal filtering method for removing noise from image sequences is proposed this method combines the use of motion compensation and signal decomposition to account for the effects of object motion because of object motion image sequences are temporally nonstationary which requires the use of adaptive filters by motion compensating the sequence prior to filtering nonstationarities i e parts of the signal that are momentarily not stationary can be reduced significantly however since not all nonstationarities can be accounted for by motion a motion compensated signal still contains nonstationarities an adaptive algorithm based on order statistics is described that decomposes the motion compensated signal into a noise free nonstationary part and a noisy stationary part an rls filter is then used to filter the noise from the stationary signal our new method is experimentally compared with various noise filtering approaches from literature