Abstract: A new optical imaging process for how to best fuse information from multiple target images into a single target image is described. The process has two primary components. First, rotating, translating and scaling each target image to register or calibrate them against a reference image and, second, determining weighing factors for each thus registered target image to select those images which add value to a final target image. The first component determines optimal rotational and translation matrices by a least squares measure using singular value decomposition. The second component determines weighing factors using correlations and statistical signal analysis techniques.

Abstract: A method for registering and fusing time-varying image sources to provide highest possible information rendering to an operator comprising the steps of aligning a plurality of image sources by matching target image to a reference image and minimizing visual registration error in a static sense and selecting target images which are best fused with a reference image using a dynamic, time-varying optimality maximum likelihood decision theory. The maximum likelihood decision theory is modified to account for time-varying using an orthogonal projection technique charactering changing density functions.

Abstract: A method of distinguishing an object in an image. The method including the steps of detecting an image with an optical device where the image includes at least one object. Identifying at least one object using a central processing unit (CPU) that includes a central processing algorithm (CPA) and uses a majority voting analysis of multiple inputs to analyze at lest one object with the CPA. The image selected by the CPU is then displayed on the optical device.