fusion methods

artificial neural networks

Inspired by the fusion of different sensor signals in biological systems, many researchers have employed artificial neural networks in the process of pixel-level image fusion.

The most popular example for the fusion of different imaging sensors in biological systems is described by Newman and Hartline in the 80s: Rattlesnakes (and the general family of pit vipers) possess so called pit organs which are sensitive to thermal radiation through a dense network of nerve fibers. The output of these pit organs is fed to the optical tectum, where it is combined with the nerve signals obtained from the eyes. Newman and Hartline distinguished six different types of bimodal neurons merging the two signals based on a sophisticated combination of suppression and enhancement.

Several researchers modeled this fusion process for the combination of multispectral imagery by a combination of several neural networks. For a detailed overview please visit the reference section.

fwd: image pyramids

bck: optimization approaches