We present an efficient algorithm for fitting three dimensional (3-D) Active Appearance Models (AAMs). We do so, by introducing a 3-D extension of a recently proposed method that is based on the inverse compositional image alignment algorithm. We demonstrate its applicability for the segmentation of the left ventricle in short axis cardiac MRI. We perform experiments to evaluate the speed and s...

Digital super resolution is a term used to describe the inverse problem of reconstructing a high resolution image from a set of known low resolution images, each of which is shifted by subpixel displacements. Simple models assume the subpixel displacements are known, but if the displacements are not known, then nonlinear approaches must be used to jointly find the displacements and the reconstr...

In order to deal with the problem of low categorization accuracy of minority class of the uneven forestry information text classification algorithm, this paper puts forward the uneven forestry information text classification algorithm based on weighted Gauss-Newton neural network, on the basis of weighted Gauss-Newton algorithm, the algorithm is proved via singular value decomposition principle...

This paper considers the issue of parameter estimation for biomedical applications using nonuniformly sampled data. The generalized linear least squares (GLLS) algorithm, first introduced by Feng and Ho (1993), is used in the medical imaging community for removal of bias when the data defining the model are correlated. GLLS provides an efficient iterative linear algorithm for the solution of th...

The phase retrieval problem is of wide interest because it appears in a number of interesting application areas in physics. Several kinds of phase retrieval problems appeared in laser optics over the past decade. In this paper we consider the numerical solution of two phase retrieval problems for an unknown smooth function f with compact support. We approximate f by a linear spline. The corresp...

The problem of constructing adaptive minimum bit error rate (MBER) decision feedback equalisers (DFEs) for binary signalling is considered. Gradient and Gauss}Newton algorithms are considered for both conventional and state (or space) translation forms of the DFE. The Hessian matrix for the Gauss}Newton algorithm is introduced for the "rst time. Kernel density estimation is demonstrated to prov...

Solving systems of nonlinear equations and inequalities is of critical importance in many engineering problems. In general, the existence of inequalities in the problem adds to its difficulty. We propose a new projected Hessian Gauss-Newton algorithm for solving general nonlinear systems of equalities and inequalities. The algorithm uses the projected Gauss-Newton Hessian in conjunction with an...

We derive a simple accuracy matching strategy for inexact Gauss Newton methods and apply it to the numerical solution of boundary value problems of ordinary diierential equations by collocation. The matching strategy is based on an aane contravariant convergence theorem, i.e., the characteristic constants are invariant under aane transformations of the domain. The inexact Gauss Newton method is...

We have developed a Bayesian model to invert spectral induced-polarization SIP data for Cole-Cole parameters using Markov-chain Monte Carlo MCMC sampling methods. We compared the performance of the MCMC-based stochastic method with an iterative Gauss-Newton-based deterministic method for Cole-Cole parameter estimation through inversion of synthetic and laboratory SIP data. The Gauss-Newton-base...

A new continuous regularized Gauss-Newton-type method with simultaneous updates of the operator (F (x(t))F (x(t)) + ε(t)I) for solving nonlinear ill-posed equations in a Hilbert space is proposed. A convergence theorem is proved. An attractive and novel feature of the proposed method is the absence of the assumptions about the location of the spectrum of the operator F (x). The absence of such ...