Hexagonal image sampling and processing are theoretically superior to the most commonly used square lattice based sampling and processing, but due to the lack of commercial image sensors, current research mainly relies on virtually hexagonally sampled data through square to hexagonal lattice conversion, which is a typical 2-D interpolation problem. This paper presents a simplified and efficient square to hexagonal lattice conversion method. The method firstly utilizes the separable nature of the interpolation kernel to simplify the original 2-D interpolation into 1-D interpolation along the horizontal direction only, and then it applies the 1-D multirate technique to further simplify the shift-variant 1-D interpolation into shift-invariant 1-D convolutions. Compared with the original 2-D interpolation version, the proposed method becomes both simple and computationally efficient, and it is also suitable for implementation with parallel processing and hardware. Finally, experiments are performed and the results are consistent with the analysis.

六边形图像采样和处理在理论上优于最常用的基于方形点阵的采样和处理，但由于缺乏商业图像传感器，目前的研究主要依赖于通过方形到六边形点阵转换的虚拟六边形采样数据，这是典型的二维插值问题。本文提出了一种简化且高效的方形到六边形点阵转换方法。该方法首先利用插值核的可分离性将原来的2-D插值简化为仅沿水平方向的1-D插值，然后应用1-D多速率技术进一步简化移位变量1-D插值到平移不变的一维卷积中。与原来的二维插值版本相比，所提出的方法变得既简单又计算效率高，并且也适用于并行处理和硬件的实现。最后进行实验，结果与分析一致。