Super-Resolution Image Reconstruction and its Simulated Experiment
超分辨率图象重构技术的仿真实验研究

Some imaging systems employ detector arrays that are not sufficiently dense to meet the Nyquist criterion during image acquisition. This is particularly true for infrared digital imagers. Therefore, the spatial resolution afforded by the optics can't be fully utilized in such imaging systems. This paper presents a new technique to reconstruct a high resolution image, with reduced aliasing, from a sequence of under sampled rotated and shifted frames of the same object. Firstly, the continuous and digital models of an imaging system are defined to explain image acquisition. Secondly, the image registration algorithm and the ordered subset conjugate gradient (OSCG) reconstruction algorithm are designed. Finally, Simulated experiment results are provided to test our algorithm, and we obtain the image whose resolution is 5 times high than the 25 under sampled frames. The results show that OSCG reconstruction algorithm is robust, rapid convergent, and memory saved.