  Clean images are an important requirement for machine vision systems to
recognize visual features correctly. However, the environment, optics,
electronics of the physical imaging systems can introduce extreme distortions
and noise in the acquired images. In this work, we explore the use of reservoir
computing, a dynamical neural network model inspired from biological systems,
in creating dynamic image filtering systems that extracts signal from noise
using inverse modeling. We discuss the possibility of implementing these
networks in hardware close to the sensors.
