基于keren改进配准算法的POCS超分辨率重建

详细介绍了keren亚象素配准算法及其不足,提出了keren算法及其迭代算法的改进算法。该算法基于简化的四参数仿射变换模型而不是传统的刚体变换模型,成功地避免了keren算法因为角度的泰勒级数展开所带来的误差,大大地提高了配准精度。实验仿真结果表明该算法与keren迭代算法相比角度绝对误差显著的降低;平移参数在15°的大角度旋转情况下获得了0.1个象素以下的绝对误差精度,在小角度的情况下获得了0.01个象素以下的绝对误差精度,最后采用POCS方法进行序列图像的高分辨率重建,实验仿真结果表明基于改进配准算法的POCS重建具有良好的配准精度和超分辨率重建效果。

POCS Super-Resolution Sequence Image Reconstruction Based on Improvement Approach of Keren Registration Method

This paper introduces the keren sub-pixel registration method in detail,and points out its disadvantage.Moreover,this paper puts forward a new improvement approach about keren method and its iterative method.The improvement approach base on the four parameters affine transformation model and refuses the rigid body transformation model.This change avoids the error that is brought on by the tailor series expansion of angle and improves the precise of image registration greatly.The experiment shows that the improvement approach makes less absolute error of angle than keren method and its iterative algorithm.The improvement approach makes the absolute error of translation parameters under 0.1 pixel in the case of the rotation angel of 15 degree and under 0.01 pixel in the case of the small rotation angle.At last,the POCS method is used to reconstruct high-resolution image from image sequences.As a result,we find that the reconstruction algorithm has good precision of image registration and good effect of super-resolution image reconstruction.