基于图像统计特征的平移线性插值方法

A Shifted Linear Interpolation Method Based on the Statistical Features of the Image

针对平移线性插值算法存在的边缘锯齿问题,提出一种基于图像统计特征的平移线性插值方法.该方法利用图像插值前后边缘统计特征的相似性,从低分辨率图像中获取估算高分辨率图像边缘点所需的协方差矩阵和矢量,并对非边缘处图像进行平移线性内插,可以同时保持图像边缘的光滑性和非边缘处的细节特征.该方法无需迭代运算,计算量较小.实验结果表明,用该方法可获得高质量的高分辨率图像.

<Abstrcat> To remove zigzag edges occurring in shift-linear interpolated image, this paper proposes an improved method based on the statistical features of the image. The basic idea is to estimate the edge pixels of the high-resolution image through the vectors and covariances obtained from its low-resolution counterpart according to their intrinsic 'geometric duality'. While nonedge pixels are got via shifted linear interpolation algorithm. No iterative computation is needed in this algorithm. The application of this new interpolation algorithm shows that it can keep the contours and details of non-edged areas.