JOINT MAP REGISTRATION AND HIGH-RESOLUTION IMAGE ESTIMATION USING A SEQUENCE OF UNDERSAMPLED IMAGES

In many imaging systems, the detector array is not sufficiently dense to adequately sample the scene with the desired field of view, This is particularly true for many infrared focal plane arrays, Thus, the res ulting images may be severely aliased, This paper examines a technique for estimating a high-resolution image, with reduced aliasing, from a sequence of undersampled frames, Several approaches to this problem h ave been investigated previously, However, in this paper a maximum a p osteriori (MAP) framework for jointly estimating image registration pa rameters and the high-resolution image is presented, Several previous approaches have relied on knowing the registration parameters a priori or have utilized registration techniques not specifically designed to treat severely aliased images, In the proposed method, the registrati on parameters are iteratively updated along with the high-resolution i mage in a cyclic coordinate-descent optimization procedure, Experiment al results are provided to illustrate the performance of the proposed MAP algorithm using both visible and infrared images, Quantitative err or analysis is provided and several images are shown for subjective ev aluation.