Multiresolution Modeling and Estimation of Multisensor Data

Modeling and estimation of multiresolution stochastic processes

An overview is provided of the several components of a research effort aimed at the development of a theory of multiresolution stochastic modeling and associated techniques for optimal multiscale statistical signal and image processing. As described, a natural framework for developing such a theory is the study of stochastic processes indexed by nodes on lattices or trees in which different dep...

Performance Modeling for Multisensor Data Fusion

With the evolution of computer and fusion algorithms, data fusion systems have been applied to many areas, both in civilian and military fields. In the past, in the multisensor fusion community, the research goal has been primarily focused on establishing a computational approach for fusion processing and algorithms. However, it will be very useful to be able to characterize the relationship be...

Unmixing-based multisensor multiresolution image fusion

Constrained and unconstrained algorithms of the multisensor multiresolution technique (MMT) are discussed. They can be applied to unmix low-resolution images using the information about their pixel composition from co-registered high-resolution images. This makes it possible to fuse the lowand high-resolution images for a synergetic interpretation. The constrained unmixing preserves all the ava...

Estimation of Generalized Multisensor

| This paper attacks the problem of generalized multisensor mixture estimation. A distribution mixture is said to be generalized when the exact nature of components is not known, but each of them belongs to a nite known set of families of distributions. Estimating such a mixture entails a supplementary diiculty: one must label, for each class and each sensor, the exact nature of the correspondi...

Modeling and Estimation for a Class of Multiresolution Random Fields