In this paper, we propose a class of nonlinear diffusion filtering based on Hammerstein function with the spline adaptive filter (HSAF) implemented by normalised version orthogonal gradient (NOGA) algorithm over distributed network. Diffusion adaptation approximates variable vector help network agents using joint optimisation sum cost function. A HSAF comprises memoryless during learning interp...

A nonlocal quadratic functional of weighted differences is examined. The weights are based on image features and represent the affinity between different pixels in the image. By prescribing different formulas for the weights, one can generalize many local and nonlocal linear denoising algorithms, including the nonlocal means filter and the bilateral filter. In this framework one can easily show...

The goal of this paper is to investigate segmentation methods that eombine fast preproeessing algorithms using partial differential equations (PD Es) with a watershed transformation with region merging. VVeeonsider two well-founded PDE methods: a nonlinear isotropie diffusion filter that permits edge enhaneement, and a eonvex nonquadratie variational image restoration method whieh gives good de...

In this paper, we propose a non-parametric method for state estimation of high-dimensional nonlinear stochastic dynamical systems. We combine diffusion maps, a manifold learning technique, with a linear Kalman filter and with concepts from Koopman operator theory. More concretely, using diffusion maps, we construct data-driven virtual state coordinates, which linearize the system model. Based o...

Ultrasound images are prone to speckle noises. Speckles blur features which are essential for diagnosis and assessment. Thus despeckling is a necessity in ultrasound image processing. Linear filters can suppress speckles, but they smooth out features. Median filter based despeckling algorithms produce better results. However, they may produce artifact patterns in the resulted images and oversmo...

improving the quality of medical images at pre and post-surgery operations are necessary for beginning and speeding up the recovery process. partial differential equations (pdes)-based models have become a powerful and well known tool in different areas of image processing such as denoising, multiscale image analysis, edge detection and other fields of image processing and computer vision. in t...

The goal of many early visual filtering processes is to remove noise while at the same time sharpening contrast. An historical succession of approaches to this problem, starting with the use of simple derivative and smoothing operators, and the subsequent realization of the relationship between scale-space and the iso-tropic diffusion equation, has recently resulted in the development of " geom...

This paper proposes a method for speckle reduction in medical ultrasound imaging while preserving the edges with the added advantages of adaptive noise filtering and speed. A nonlinear image diffusion method that incorporates local image parameter, namely, scatterer density in addition to gradient, to weight the nonlinear diffusion process, is proposed. The method was tested for the isotropic c...

Recursive filtering structures reduce drastically the computational effort required for different tasks in image processing. These operations are done with a fixed number of operations per output point independently of the size of the neighbourhood considered. In this paper we show that implicit numerical implementations of some partial differential equations (PDE’s) provide algorithms that can...