The infrared imaging research has been supported in part under Air Force contract F33601-95-DJ010. The research has been done in conjunction with Wright Labs Sensor Technology Branch (WL/AAJT) and the FLIR team members involved.
Some imaging systems employ detector arrays which are not sufficiently dense so as to meet the Nyquist 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. We want to enhance the resolution of such imaging systems.
This research has developed 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 be obtained if an imager is mounted on a moving platform, such as an aircraft.
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. Several images are shown for subjective evaluation below.
Mirrored from Russ Hardie's homepage