Abstract. We study a functional with variable exponent, 1 ≤ p(x) ≤ 2, which provides a model for image denoising, enhancement, and restoration. The diffusion resulting from the proposed model is a combination of total variation (TV)-based regularization and Gaussian smoothing. The existence, uniqueness, and long-time behavior of the proposed model are established. Experimental results illustrat...

The applications of object-based image analysis (OBIA) in remote sensing studies of wetlands have been growing over recent decades, addressing tasks from detection and delineation of wetland bodies to comprehensive analyses of within-wetland cover types and their change. Compared to pixel-based approaches, OBIA offers several important benefits to wetland analyses related to smoothing of the lo...

This paper proposes two techniques for the enhancement of the performance of the Linear Minimum Mean Square Error (LMMSE) or Wiener restoration algorithm. The first approach relies on adaptively merging the Wiener restoration algorithm with a regularized restoration algorithm that is implemented iteratively. The merging process allows the capturing of edges regions from the Wiener restoration r...

In this paper, we compare two restoration techniques applied to 3D angiographies and to femoral CT scans. The rst technique uses a Partial Derivative Equation and the second one is based on an extension of adaptive Wiener lters. We rst present each method. Then, we discuss and compare the estimation of the local orientations in 3D images obtained either by the smoothed gradient and the principa...

In this paper we address the problem of redving blurred point sources in intensity images. A new approach to image restoration is introduced which is a 2-D generalization uf techniques originating from the field of direction of arrival estimation (DOA). I n the 2-D frequency domain. algorithms, such as MUSIC. may be adapted to search for these point sources. A generalization of array smoothing ...

A generalization of the linear fractional integral equation u(t) = u0 + ∂−αAu(t), 1 < α < 2, which is written as a Volterra matrix–valued equation when applied as a pixel–by–pixel technique, has been proposed for image denoising (restoration, smoothing,...). Since the fractional integral equation interpolates a linear parabolic equation and a hyperbolic equation, the solution enjoys intermediat...

Abstract. We introduce and investigate the modified TV-Stokes model for two classical image processing tasks, i.e., image restoration and image inpainting. The modified TV-Stokes model is a two-step model based on a total variation (TV) minimization in each step and the use of geometric information of the image. In the first step, a smoothed and divergence free tangential field of the given ima...

In this paper we study the partial regularity of a functional on BV space proposed by Chambolle and Lions [3] for the purposes of image restoration. The functional is designed to smooth corrupted images using isotropic diffusion via the Laplacian where the gradients of the image are below a certain threshold and retain edges where gradients are above the threshold using the total variation. Her...

An effective nonlinear second-order PDE image denoising and restoration model is described in this paper. The proposed anisotropic diffusion-based filtering scheme is based on some novel versions of the edge-stopping function and the conductance parameter. A consistent numerical approximation scheme is constructed for this continuous model. Our PDE-based smoothing technique provides an efficien...

In this paper, we develop a recursive model-based maximum a posteriori (MAP) estimator that simultaneously e& timates the displacement vector field (DVF) and intensity field from a noisy-blurred image sequence. Current motioncompensated spatio-temporal filters treat the estimation of the DVF as a preprocessing step. Thereby, no attempt is made to verify the accuracy of these estimates prior to ...