Various structures in human physiology follow a treelike morphology, which often expresses
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …

Reviews a significant component of the rich field of statistical multiresolution (MR) modeling
and processing. These MR methods have found application and permeated the literature of …

This monograph gives an introduction to the fundamentals of Markovian modeling in image
segmentation as well as a brief overview of recent advances in the field. Segmentation is …

In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images
is of interest for many brain disorders. However, due to several factors such as noise …

This letter addresses the problem of classifying synthetic aperture radar (SAR) images of
urban areas by using a supervised Bayesian classification method via a contextual …

In this paper, we develop a novel classification approach for multiresolution, multisensor
[optical and synthetic aperture radar (SAR)], and/or multiband images. This challenging …

This paper deals with the problem of unsupervised classification of images modeled by
Markov random fields (MRF). If the model parameters are known then we have various …

The deconvolution of blurred and noisy satellite images is an ill-posed inverse problem.
Donoho (1994) has proposed to deconvolve the image without regularization and to …

Markovian approaches to early vision processes need a huge amount of computing power.
These algorithms can usually be implemented on parallel computing structures. Herein, we …

This paper presents an unsupervised method to segment multispectral images, involving a
correlated non-Gaussian noise. The efficiency of the Markovian quadtree-based method we …