一种基于去混叠影像配准方法的POCS超分辨率序列图像重建

简要介绍超分辨率重建的原理和数学模型,采用一种新的超分辨率重建算法,这种算法通过去除低分辨率影像由于欠采样而产生的频率混叠部分以及频率中心的部分低频,来实现图像的精确配准;在计算旋转角度时,通过在图像中心建立极坐标系,求取设定角度精度范围内关于幅度谱的函数,将2维的相关函数转换成1维相关,大大提高计算效率;最后该算法采用POCS方法进行序列图像的高分辨率重建。实验仿真结果表明该算法具有良好的配准精度和超分辨率重建效果,具有良好的应用价值。

POCS Super-resolution Sequence Image Reconstruction Based on Image Registration Excluded Aliased Frequency Domain

The theory of super-resolution image reconstruction and degraded model, is introduced in brief, and presents a new super-resolution image reconstruction algorithm . The algorithm can precisely estimate the image registration parameter by excluding aliased frequency domain of the low resolution images and killing the center part of the magnitude spectrum. In order to compute the shifts and the rotation angle, we set up the polar coordinates in the center of the image. By computing the frequency content h as a function of the angle a by integrating over radial lines, the algorithm converts the two-dimension correlation to one-dimension correlation. At last, the POCS method is used to reconstruct high-resolution image from these aliased 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.