Delaunay三角剖分插值用于超分辨成像

Delaunay Triangulation Interpolation Used in Super-Resolution Imaging

  • 摘要: 微变焦超分辨成像在插值重建方面比较困难,目前基于最小二乘估计的频域模型和空域模型也都存在一些局限性。为了兼顾超分辨成像的实时性和精确性,该文在图像重建过程中,借鉴Delaunay三角剖分的数学概念,采用随机增量算法,定义了基于Delaunay三角剖分的插值算法。该算法可以提高分辨率,降低运算量。仿真实验结果表明,该算法在图像重建的时间和均方误差方面,均优于共轭梯度最小二乘法,其中基于Delaunay三角剖分的三次方插值算法的优越性更为突出。

     

    Abstract: micro zooming super-resolution imaging is difficult for interpolation and reconstruction, and there are some limitations in the frequency domain model and space domain model based on LSE (least squares estimation). By referring to the mathematical concept of Delaunay triangulation and randomized incremental algorithm, an interpolation algorithm based on Delaunay triangulation in the course of image reconstruction is defined for both real time and accuracy of super-resolution imaging. This algorithm can improve the resolution and reduce the amount of calculation. The results of simulation experiment show that this method is better than the method based on conjugate gradient least square (CGLS) in the speed and error of image reconstruction.

     

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