Showing papers by "Fernand Meyer published in 2005"

Image Filtering Using Morphological Amoebas

Abstract: This article presents the use of anisotropic dynamic structuring elements, or amoebas, in order to build content-aware noise reduction filters. The amoeba is the ball defined by a special geodesic distance computed for each pixel, and can be used as a kernel for many kinds of filters and morphological operators. 1. Introduction Noise is possibly the most annoying problem in the field of image processing. There are two ways to work around it: either design particularly robust algorithms that can work in noisy environments, or try to eliminate the noise in a first step while losing as little relevant information as possible and consequently use a normally robust algorithm. There are of course many algorithms that aim at reducing the amount of noise in images. In mathematical morphology filters can be, broadly-speaking, divided into two groups: 1 alternate sequential filters based on morphological openings and clos-ings, that are quite effective but also remove thin elements such as canals or peninsulas. Even worse, they can displace the contours and thus create additional problems in a segmentation application.

Hierarchical watersheds within the combinatorial pyramid framework

Abstract: Watershed is one of the most popular tool defined by mathematical morphology. The algorithms which implement the watershed transform generally produce an over segmentation which includes the right image's boundaries. Based on this last assumption, the segmentation problem turns out to be equivalent to a proper valuation of the saliency of each contour. Using such a measure, hierarchical watershed algorithms use the edge's saliency conjointly with statistical tests to decimate the initial partition. On the other hand, Irregular Pyramids encode a stack of successively reduced partitions. Combinatorial Pyramids consitute the latest model of this family. Within this framework, each partition is encoded by a combinatorial map which encodes all topological relationships between regions such as multiple boundaries and inclusion relationships. Moreover, the combinatorial pyramid framework provides a direct access to the embedding of the image's boundaries. We present in this paper a hierarchical watershed algorithm based on combinatorial pyramids. Our method overcomes the problems connected to the presence of noise both within the basins and along the watershed contours.

Space, Structure and Randomness

Abstract: Space, structure and randomness , Space, structure and randomness , کتابخانه دیجیتال جندی شاپور اهواز

Grey-Weighted, Ultrametric and Lexicographic Distances

Abstract: Shortest distances, grey weighted distances and ultrametric distance are classically used in mathematical morphology We introduce a lexicographic distance, for which any segmentation with markers becomes a Voronoi tessellation

Space, structure and randomness : contributions in honor of Georges Matheron in the field of geostatistics, random sets and mathematical morphology

Abstract: Personal reminiscences of Georges Matheron, Dietrich Stoyan.- A few words about Georges Matheron (1930-2000), Jean Serra.- Introduction.- The genesis of geostatistics in gold and diamond industries, Danie Krige, Wynand Kleingeld.- Concepts and methods of geostatistics, Jacques Rivoirard.- Prediction by conditional simulation: models and algorithms, Jean-Paul Chiles, Christian Lantuejoul.- Flow in porous media: an attempt to outline Georges Matheron's contributions, J.P. Delhomme, G. de Marsily.- Over thirty years of petroleum geostatistics, Pierre Delfiner, Andre Haas.- The expansion of environmental geostatistics, Roberto Bruno, Chantal de Fouquet.- Random closed sets, I. Molchanov.- The Boolean model: from Matheron till Today, Dietrich Stoyan, Klaus Mecke.- Random structures in physics, Dominique Jeulin.- Mophological operatorors for the segmentation of colour images, Jean Serra.- Automatic design of morphological operators, Junior Barrera, Gerald J.F. Banon, Edward R. Dougherty.- Morphological decomposition systems with perfect reconstruction: from pyramids to wavelets, Henk J.A.M. Heijmans, John Goutsias.- Morphological segmentation revisited, Fernand Meyer.- Ubiquity of the distance function in mathematical morphology, Michel Schmitt.- Partial differential equations for morphological operators, Frederic Guichard, Petros Maragos, Jean-Michel Morel.

Noise reduction in 3D images using morphological amoebas

Abstract: This article presents the use of morphological amoebas for the enhancement of 3D medical images. Morphological amoebas are kernels adapting their shape in such a way that they do not cross the contours of the image. They can be used in morphological operations in quite a similar way as classical kernel and are well-fitted for noise-reduction in 3D medical images.