一种分区域多方向数据融合图像插值方法

为满足高端工业检测中对检测精度和检测时间的严格要求，针对现有图像插值方法在插值速度与精度方面的矛盾，本文提出了一种分区域多方向数据融合图像插值方法。在灰度平坦区域，采用双线性插值算法进行插值。在边缘纹理区域，则选取待插值点在源图像中对应点的4×4邻域内4个插值方向上距离最近的12个像素点，基于距离平方反比计算估计值；然后结合方向灰度梯度和插值距离两个权 重因子，进行数据融合，获得最终插值。实验表明，新提出的插值方法运行速度快，并且在图像任意级别变换时都具有较高的插值精度，能够很好地保持图像的边缘纹理细节。

New Image Interpolation Method Based on Sub-regional and Multi-directional Data Fusion

To solve the contradictory of speed and accuracy of the existing interpolation method, an interpolation method based on sub-regional and multi-directional data fusion is presented. The new method divides images into flat areas and edge-regions. The bilinear algorithm is used in flat areas, and the improved algorithm is used in edge-regions. Based on the inverse ratio of the distance square, the improved algorithm fully considers four-direction estimated results of the nearest horizontal, vertical and two diagonal directions using 12 pixels selected from 4×4 neighborhood. A final interpolation result is obtained by calculating weights of vertical distance and direction gradient. The experimental result shows that the proposed interpolation method costs less time and can make edges of image more natural and clear. Moreover, it can be applied to any multiples of interpolation amplification.