High resolution infrared image reconstruction using multiple, low resolution, aliased frames

Staring infrared detectors often produce low resolution images. This problem arises simply because the technology does not exist to produce higher resolution arrays with sufficient spatial sampling intervals. A proven approach to combat this difficulty involves recording multiple frames that have been optically shifted onto a high-resolution grid pattern and then combined together into a single high resolution image. This process is known as microscanning. In fact, if the infrared (IR) imaging system is mounted on a moving platform, the normal vibrations associated with the platform´s movement can be exploited to generate shifts in the acquired images. We present an algorithm that can register this temporal image sequence at the sub pixel level and then reconstruct a high resolution image from the shifted frames. The proposed algorithm uses a gradient based shift estimator which provides shift information for each of the recorded frames. The reconstruction algorithm is based on a technique of high resolution image reconstruction by solving a series of linear equations in the frequency domain. In this paper, we review the theory behind the registration and reconstruction algorithms and their limitations. We demonstrate that the registration is a viable real-time algorithm that is suitable for applications involving small image shifts (i.e. less than one detector element). We also show that the reconstruction program gives dramatic improvements in the image´s resolution and does well in handling the aliased information