Bayesian MAP (maximum a posteriori) methods for SPECT reconstruction can both stabilize reconstructions and lead to better bias and variance relative to ML methods. In previous work [1], a nonquadratic prior (the weak plate) that imposed piecewise smoothness on the first derivative of the solution led to much improved bias/variance behavior relative to results obtained using a more conventional...

The existing system available for fuzzy filters for noise reduction deals with fat-tailed noise like impulse noise and median filter. Only impulse noise reduction uses fuzzy filters. Gaussian noise is not specially concentrated; it does not distinguish local variation due to noise and due to image structure. The proposed system presents a new technique for filtering narrow-tailed and medium nar...

We propose an accurate tracking algorithm based on a multi-feature statistical model. The model combines in a single particle filter colour and gradient-based orientation information. A reliability measure derived from the particle distribution is used to adaptively weigh the contribution of the two features. Furthermore, information from the tracker is used to set the dimension of the filters ...

This paper discusses the extension of nonlinear diffusion filters to higher derivative orders. While such processes can be useful in practice, their theoretical properties are only partly understood so far. We establish important results concerning L-stability and forwardbackward diffusion properties which are related to well-posedness questions. Stability in the L-norm is proven for nonlinear ...

We develop a learning rule for networks of spiking neurons where signals are encoded using fractionally predictive spike-coding. In this paradigm, neural output signals are encoded as a sum of shifted power-law kernels. Simple greedy thresholding can compute this encoding, and spike-trains are then exactly the signal’s fractional derivative. Fractionally predictive spike-coding exploits natural...

This paper focuses on the convergence rate and numerical characteristics of the nonlinear information consensus filter for object tracking using a distributed sensor network. To avoid the Jacobian calculation, improve the numerical characteristic and achieve more accurate estimation results for nonlinear distributed estimation, we introduce square-root extensions of derivative-free information ...

the aim of this study was to evaluate the effect of evaporative media as gas turbine intake air cooling method on pressure drop of cartridge air filters. this study performed under the laboratory condition, using stainless steel test rig with specified dimensions to investigate the role of evaporative media in air cooling as well as its effects on new and used cartridge filters (as representati...

Gaussian filter has been used extensively in signal image processing for many years. Gaussian or Gaussian derivative filtering is in several ways optimal for applications requiring low-pass filters or running averages. In this paper, a highly efficient noise removing technique based on a modified dynamic Gaussian filter is introduced. Called smooth filter, the Gaussian filter is known to be mor...

This paper deals with steerable filters in context of motion estimation. Whereas the classical brightness constancy constraint equation (BCCE) connects the optical flow with the first order directional derivative filter of the observed signal, we abstract to the most general class of filters nullifying the signal when applied in the direction of motion. We developed a method to adjust linear co...