Abstract: Image interpolation is an important method to magnify images with low resolution to adapt to the target screens. To preserve the geometry feature of the original image is an effective way to improve the quality of magnified images. This paper proposed a new method to interpolate images based on Doo Sabin subdivision. The method adopted the essential idea of subdividing the quadrilateral mesh to enhance the sampling images of low resolution. Firstly, part of the data of high resolution images was obtained by mapping low resolution images. Secondly we classified the unknown pixels of high resolution images according to their geometric features. Then we interpolated all the unknown pixels by the assigned pixels. Values of the unknown pixels were the weighted average of their neighboring pixels. The weighted strategy was deduced by Doo Sabin subdivision. Experiments show that our method can preserve the sharp feature of image edges, decrease zigzags and achieve better results than the previous methods.

Key words: Doo Sabin subdivision, image interpolation, zigzag, magnification, geometry feature

摘要： 图像插值是放大低分辨率图像以适应目标显示屏幕的一种重要方法。保持图像的几何特征是保证放大图像质量的一个有效途径。基于Doo Sabin细分,提出了一种新的图像插值方法。该方法首先通过一次映射关系获取高分辨图像的部分数据;然后根据高分辨率图像中未知像素点的几何特征将它们分类;再根据Doo Sabin细分方法由已知像素点插值出所有未知像素点。未知像素点的值是与最相关的邻近像素点的加权均值,加权策略根据像素点间的相对位置由Doo Sabin细分推演获得。实验证明,与现有插值方法相比,基于Doo Sabin细分的图像插值能够更好地保持上采样图像的边缘的尖锐特性,减少锯齿现象,获取高质量的高分辨率图像。

关键词: Doo Sabin细分, 图像插值, 锯齿, 放大, 几何特征