Image formation from severely undersampled scalar infrared data sets

The author describes the formation of an image from no more than ten (and usually fewer) scalar sensor readings. An infrared (IR) signal source is assumed, placing unusual demands on signal estimation and image construction algorithms. An onion-growth image construction algorithm that generates a single binary image object consistent with sensor measurements is presented. It is so called because it identifies an approximate center of mass, or seed pixel, and then grows a series of concentric circles around the seed pixel. Synthetic object studies illustrate the effectiveness of the image construction algorithm and demonstrate that, image artifacts are suppressed or eliminated by using the largest possible sensor field of view