已有的边缘方向插值算法利用高低分辨率图像局部方差之间存在的对偶性实现自适应非线性插值。其性能明显优于传统线性插值算法，但图像边缘噪声可能仍然比较明显。为了获得更好的视觉效果。提出了一种改进算法。充分利用局部降采样像素之间的相关信息，用和被插点相邻的6个降采样像素估计高分辨率图像的局部协方差。该算法应用于灰度和彩色图像的分辨率增强，不仅降低了运算复杂度，而且有效地抑制了边缘噪声，进一步提高了插值图像的视觉质量。

Regarding the inherent drawbacks of linear interpolation (edge blurring or artifact), nonlinear interpolation technique is studied in this paper. Existing new edge-directed interpolation algorithm utilizes the duality between high-resolution covariance and its low-resolution counterpart to realize adaptive nonlinear interpolation and obtains a much better visual quality of interpolated images than traditional linear interpolations. But interpolated images may still suffer from blurring edges or introducing artifacts around edge area. To achieve a better subjective quality, an improved algorithm is proposed in this paper. It makes full use of local relative information in the low-resolution image. Six downsampled neighbors are involved to estimate local covariance characteristics at high resolution. Two important applications of the algorithm are investigated: resolution enhancement of grayscale images and reconstruction of color images. Experimental results demonstrate that the improved algorithm not only decreases the computational complexity but also succeeds in reducing artifacts on the edges and substantially improves the visual quality of the interpolated images over conventional linear interpolation.