High Resolution Image Reconstruction: High Resolution Image Reconstruction from aSequence of Rotated and Translated Frames

摘要

Some imaging sytems employ detector arrays which are not dense enough to meet theNyquist criteria during image acquisition. This is particularly true for many staring infrared imagers. Thus, the full resolution afforded by the optics is not being realized in such a system. This paper presents a technique for estimating a high resolution image, with reduced aliasing, from a sequence of undersampled rotated and translationally shifted frames. Such an image sequence can can be obtained if an imager is mounted on a moving platform, such as an aircraft. Several approaches to this problem have been proposed in the literature. Here we extend some of this previous work. In particular, we define an observation model which incorporates accurate knowledge of the optical system. The high resolution image estimate is formed by minimizing a regularized cost function which is based on the observation model. We consider both gradient descent and conjugate gradient optimization procedures to minimize the cost function. We show that the conjugate gradient optimization provides rapid convergence. Detailed experimental results are provided to illustrate the performance of the proposed algorithm using both visible and infrared images.