Color Night Vision: Opponent Processing in the Fusion of Visible and IR Imagery.

We describe here a means of fusing registered low-light visible and thermal infrared (IR) imagery to support realtime color night vision. Opponent processing, in the form of feedforward center-surround shunting neural networks, is used to contrast enhance and adaptively normalize both visible and IR imagery separately. Both positive and negative polarity ("on" and "off") enhanced IR imagery is then combined with the enhanced visible imagery to create two single-opponent color-contrast grayscale images.