Shift estimation and non-uniformity in sequences of scene images

Most non-conventional approaches to image restoration of scenes observed over long atmospheric slant paths require multiple frames of short exposure images taken with low noise focal plane arrays. The individual pixels in these arrays often exhibit spatial non-uniformity in their response. In addition base motion jitter in the observing platform introduces a frame-to-frame linear shift that must be compensated for in order for the multi-frame restoration to be successful. In this paper we describe a maximum a-posteriori parameter estimation approach to the simultaneous estimation of the frame-to-frame shifts and the array non-uniformity. This approach can be incorporated into an iterative algorithm and implemented in real time as the image data is being collected. We present a brief derivation of the algorithm as well as its application to actual image data collected from an airborne platform.