The principle of the iterated extended Kalman filter has been generalized to create a new filter that has superior performance when the estimation problem contains severe nonlinearities. The new filter is useful when nonlinearities might significantly degrade the accuracy or convergence reliability of other filters. The new filter solves a nonlinear smoothing problem for the current and past sa...

This paper presents a Gaussian noise filter that uses a sigmoid shaped membership function to model image information in the spatial domain. This function acts as a tunable smoothing intensification operator. With a proper choice of two sigmoid parameters ‘t’ and ‘a’, the filter strength can be tuned for removal of Gaussian noise in intensity images. An image information measure, Total Compatib...

Annihilation or reduction of each kind of noise blended in correct data signals is a field that has attracted many researchers. It is a fact that fuzzy theory presents full capability in this field. Fuzzy filters are often strong in smoothing corrupted signals, whereas they have simple structures. In this paper, a new powerful yet simple fuzzy procedure is introduced for sharpness reduction in ...

Bilateral filtering is widely used to enhance photographic images, but in most implementations is poorly suited to seismic images. A bilateral filter consists of two (domain and range) filter kernels. By replacing the domain kernel with a smoothing filter that conforms to image structures, we obtain a bilateral filter suitable for seismic image processing. Examples and comparison with conventio...

In this paper, we introduce a new mesh filtering method: a mesh median filter. This is an application of the median filter to smoothen 3-D noisy shapes given by triangle meshes. An algorithm of the mesh median filter is realized by applying the median filter to face normals on triangle meshes and updating mesh vertex positions to make them fit to the filtered normals. As an advanced modificatio...

Noncausal estimation algorithms, which involve smoothing, can be used for off-line identification of nonstationary systems. Since smoothing is based on both past and future data, it offers increased accuracy compared to causal (tracking) estimation schemes, incorporating past data only. It is shown that efficient smoothing variants of the popular exponentially weighted least squares and Kalman ...

This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely ...

The problem of constructing and approximating control theoretic smoothing splines is considered in this paper. It is shown that the optimal approximating function can be given as the solution of a forced Hamiltonian system, that can be explicitly solved using the Riccati transform, and an explicit linear filter can be constructed. We show that the bandwidth of the filter can be naturally contro...

The paper is devoted to the smoothing of discrete functions using the fuzzy transform (shortly, Ftransform) introduced by Perfilieva in [1]. We generalize a smoothing filter based on the fuzzy transform proposed in [2] to obtain a better control on the smoothed functions. For this purpose, a generalization of the concept of fuzzy partition is suggested and the smoothing filter is defined as a c...

This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely ...