Reactiondiffusion network for geometric multiscale high speed image processing
In the framework of heavy mid-level processing for high speed imaging, a nonlinear bi-dimensional network is proposed, allowing the implementation of active curve algorithms. Usually this efficient type of algorithm is prohibitive for real-time image processing due to its calculus charge and the inadequate structure for the use of serial or parallel architectures. Another kind of implementation philosophy is proposed here, by considering the active curve generated by a propagation phenomenon inspired from biological modeling. A programmable nonlinear reactiondiffusion system is proposed under front control and technological constraints. Geometric multiscale processing is presented and this opens a discussion about electronic implementation.
image analysis multiscale geometry nonlinear signal processing