COLOR NIGHT-VISION - OPPONENT PROCESSING IN THE FUSION OF VISIBLE ANDIR IMAGERY

We describe here a means of fusing registered low-light visible and th ermal infrared (IR) imagery to support realtime color night vision. Op ponent 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 po larity (''on'' and ''off'') enhanced IR imagery is then combined with the enhanced visible imagery to create two single-opponent color-contr ast grayscale images. The opponent processed visible and opponent-colo r images (forming a set of three grayscale images) are then assigned d irectly to the red, green, blue (RGB) color space. Final manipulation of both hue and saturation is achieved in the hue, saturation, value ( HSV) color space. Remarkably realistic color renderings of night scene s are obtained which may support perceptual ''pop-out'' of extended na vigation cues and compact targets. Psychophysical testing on low contr ast targets in natural dynamic scenes is called for in order to assess human performance using fused visible and IR imagery at night. Copyri ght (C) 1996 Elsevier Science Ltd.