Polynomial interpolation and approximation methods on sampling points along Lissajous curves using Chebyshev series is an effective way for a fast image reconstruction in Magnetic Particle Imaging. Due to the nature of spectral methods, a Gibbs phenomenon occurs in the reconstructed image if the underlying function has discontinuities. A possible solution for this problem are spectral filtering...

background: butterworth, gaussian, hamming, hanning, and parzen are commonly used spect filters during filtered back-projection (fbp) reconstruction, which greatly affect the quality and size accuracy of image. materials and methods: this study involved a cardiac phantom in which 1.10 cm thick cold defect was inserted into its myocardium wall and filled with 4.0 μci/ml (0.148 mbq/ml) 99mtc conc...

A new deconvolution algorithm for binary images based on the theory of discrete tomography is proposed. The proposed algorithm is inherently binary as opposed to traditional filtering techniques such as Wiener filtering which require thresholding to produce binary images. Time and space complexity of the proposed algorithm are polynomial in the image size whereas the two-dimensional Viterbi met...

We study the linear filtering problem for systems driven by continuous Gaussian processes V (1) and V (2) with memory described by two parameters. The processes V ( j) have the virtue that they possess stationary increments and simple semimartingale representations simultaneously. They allow for straightforward parameter estimations. After giving the semimartingale representations of V ( j) by ...

The problem of generalized 2D FIR filtering for large filter kernel sizes can be computationally prohibitive when required in real-time, such as with video applications. In this paper, we describe architectures and design methods for generalized 2D FIR filtering employing LOGIC Devices' LF33xx (HV Filter) family of devices. The LF33xx family of devices is designed to perform dimensionally separ...

We study the linear filtering problem for systems driven by continuous Gaussian processes V 1 and V 2 with memory described by two parameters. The processes V j have the virtue that they possess stationary increments and simple semimartingale representations simultaneously. It allows for straightforward parameter estimations. After giving the semimartingale representations of V j by innovation ...

Image processing researchers commonly assert that “median filtering is better than linear filtering for removing noise in the presence of edges.” Using a straightforward large-n decision-theory framework, this folk-theorem is seen to be false in general. We show that median filtering and linear filtering have similar asymptotic worst-case meansquared error (MSE) when the signal-to-noise ratio (...

We study the linear filtering problem for systems driven by continuous Gaussian processes V1 and V2 with memory described by two parameters. The processes Vj have the virtue that they possess stationary increments and simple semimartingale representations simultaneously. It allows for straightforward parameter estimations. After giving the semimartingale representations of Vj by innovation theo...

This paper is concerned with the receding horizon filtering problem for a class of discrete time-varying nonlinear systems with multiple missing measurements. The phenomenon of missing measurements occurs in a random way and the missing probability is governed by a set of stochastic variables obeying the given Bernoulli distribution. By exploiting the projection theory combined with stochastic ...