We describe an automated edge enhancement procedure that operates in conjunction with clustereddot dithering, edge weighted unsharp masking, compound anisotropic diffusion etc. The goal is to make weak edges more noticeable and to give the strong edges in the half toned image a sharper and more natural appearance. Unsharp masking that is widely used for image enhancement amplifies image contras...

Speckle noise is supposed to be dependent on the signal intensity in the sense that the noise level increases with the brightness. Many approaches have been proposed to reduce the speckle effect in coherent imaging. Early works used the adaptive filters based on linear minimum mean square error by taking local statistics. The best-known filters include the Lee filter[1], Frost filter[2], Kuan f...

We present and evaluate a bilateral filter for smoothing diffusion MRI fiber orientations with preservation of anatomical boundaries and support for multiple fibers per voxel. Two challenges in the process are the geometric structure of fiber orientations and the combinatorial problem of matching multiple fibers across voxels. To address these issues, we define distances and local estimators of...

We are presenting here a model for processing space-time image sequences and applying them to 3D echo-cardiography. The non-linear evolutionary equations filter the sequence with keeping space-time coherent structures. They have been developed using ideas of regularized Perona-Malik an-isotropic diffusion and geometrical diffusion of mean curvature flow type (Malladi-Sethian), combined with Gal...

In conventional distributed Kalman filtering, employing diffusion strategies, each node transmits its state estimate to all its direct neighbors in each iteration. In this paper we propose a partial diffusion Kalman filter (PDKF) for state estimation of linear dynamic systems. In the PDKF algorithm every node (agent) is allowed to share only a subset of its intermediate estimate vectors at each...

In this paper, we present a new method for removing texture in color images using a smoothing rotating filter. From this filter, a bank of smoothed images provides pixel signals for each channel image able to classify a pixel belonging to a texture region. We apply this classification in each channel image in order to compute two directions for the anisotropic diffusion. Then, we introduce a ne...

Visual object tracking is the active area of research in the computer vision. Various techniques have being developed for the object tracking .Particle filter deals with the tracking of the objects having non linear motion .Particle filter has been used in for various fields and application efficiently. Proposed Technique is based on combination of kalman filter, mean shift and particle filter....

Diffusion processes are often regarded as among the more abstruse stochastic processes, but diffusion processes are actually relatively elementary, and thus are natural first candidates to consider in queueing applications. To help demonstrate the advantages of diffusion processes, we show that there is a large class of one-dimensional diffusion processes for which it is possible to give conven...

The Kalman filter is the optimal minimum-variance state estimator for linear dynamic systems with Gaussian noise. In addition, the Kalman filter is the optimal linear state estimator for linear dynamic systems with non-Gaussian noise. For nonlinear systems various modifications of the Kalman filter (e.g., the extended Kalman filter, the unscented Kalman filter, and the particle filter) have bee...