The increasing computing power of modern smartphones opens the door for interesting mobile image analysis applications. In this paper, we explore the arising possibilities but also discuss remaining challenges by implementing linear and nonlinear diffusion filters as well as basic variational optic flow approaches on a modern Android smartphone. To achieve low runtimes, we present a fast method...

Non-linear diffusion or Variable Conductance Diffusion (VCD) processes can be used as to filter away noise while preserving boundary information. However, adjustment of the control parameters is not well understood. By approaching the control of VCD systems through a multiscale statistical analysis, information about the image is revealed regarding the strength of boundaries and their influence...

Diffusion magnetic resonance imaging (dMRI) has become an established research tool for the investigation of tissue structure and orientation. In this paper, we present a method for real-time processing of diffusion tensor and Q-ball imaging. The basic idea is to use Kalman filtering framework to fit either the linear tensor or Q-ball model. Because the Kalman filter is designed to be an increm...

Conventional error diffusion halftoning uses a causal error filter. We propose the iterative error diffusion algorithm by extending the error diffusion to accommodate noncausal error filters. We realize the importance of the phase response of the error filter in the error diffusion halftoning method, and demonstrate it using examples. Iterative error diffusion is able to realize a zero phase er...

Stabilization using filters is intended to model and extract the energy lost to resolved scales due to nonlinearity breaking down resolved scales to unresolved scales. This process is highly nonlinear and yet current models for it use linear filters to select the eddies that will be damped. In this report we consider for the first time nonlinear filters which select eddies for damping (simulati...

We consider the filtering problem for linear models where the driving noises may be quite general, non-white and non-Gaussian, and where the observation noise may only be known to belong to a finite family of possible disturbances. Using diffusion approximation methods, we show that a certain nonlinear filter minimizes the asymptotic filter variance. This nonlinear filter is obtained by choosin...

one of the common problems in reflective seismic records is the existence of coherent linear and random noises which cause covering of the most important parts of reflective signals; therefore, it is necessary to attenuate them by processing methods. several processing techniques have been devised for attenuation of coherent linear noises and linear radon or ?-? transform is a powerful techniqu...

the aim of this paper is to improve the performance of the conventional goertzel algorithm in determining the protein codingregions in deoxyribonucleic acid (dna) sequences. first, the symbolic dna sequences are converted into numerical signals usingelectron ion interaction potential method. then by combining the modified anti-notch filter and linear predictive coding model,we proposed an effic...

A method is proposed to enhance vascular structures within the framework of scale space theory. We combine a smooth vessel filter which is based on a geometrical analysis of the Hessian's eigensystem, with a non-linear anisotropic diffusion scheme. The amount and orientation of diffusion depend on the local vessel likeliness. Vessel enhancing diffusion (VED) is applied to patient and phantom da...

The starting point for this paper is the well known equivalence between convolution filtering with a rescaled Gaussian and the solution of the heat equation. In the first chapters we analyze the equivalence between multiscale convolution filtering, linear smoothing methods based on continuous wavelet transforms and the solutions of linear diffusion equations. I.e. we determine a wavelet ψ, resp...