This paper introduces an image interpolation method that provides performance superior to that of the state-of-the-art algorithms. The simple linear method, if used for interpolation, provides interpolation at the cost of blurring, jagging, and other artifacts; however, applying complex methods provides better interpolation results, but sometimes they fail to preserve some specific edge patterns or results in oversmoothing of the edges due to postprocessing of the initial interpolation process. The proposed method uses a new gradient-based approach that makes an intelligent decision based on the edge direction using the edge map and gradient map of an image and interpolates unknown pixels in the predicted direction using known intensity pixels. The input image is subjected to the efficient hysteresis thresholding-based edge map calculation, followed by interpolation of low-resolution edge map to obtain a high-resolution edge map. Edge map interpolation is followed by classification of unknown pixels into obvious edges, uniform regions, and transitional edges using the decision support system. Coefficient-based interpolation that involves gradient coefficient and distance coefficient is applied to obvious edge pixels in the high-resolution image, whereas transitional edges in the neighborhood of an obvious edge are interpolated in the same direction to provide uniform interpolation. Simple line averaging is applied to pixels that are not detected as an edge to decrease the complexity of the proposed method. Applying line averaging to smooth pixels helps to control the complexity of the algorithm, whereas applying gradient-based interpolation preserves edges and hence results in better performance at reasonable complexity.

中文翻译：

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基于梯度相关的边缘方向估计的图像插值

本文介绍了一种图像插值方法，其性能优于最先进算法的性能。简单的线性方法，如果用于插值，会以模糊、锯齿和其他伪影为代价提供插值；然而，应用复杂的方法可以提供更好的插值结果，但有时它们无法保留某些特定的边缘模式或由于初始插值过程的后处理而导致边缘过度平滑。所提出的方法使用一种新的基于梯度的方法，该方法使用图像的边缘图和梯度图基于边缘方向做出智能决策，并使用已知强度像素在预测方向上插值未知像素。输入图像经过高效的基于滞后阈值的边缘图计算，然后对低分辨率边缘图进行插值，得到高分辨率边缘图。边缘图插值之后是使用决策支持系统将未知像素分类为明显边缘、均匀区域和过渡边缘。对高分辨率图像中的明显边缘像素应用涉及梯度系数和距离系数的基于系数的插值，而在明显边缘附近的过渡边缘沿相同方向插值以提供均匀插值。简单的线平均应用于未被检测为边缘的像素，以降低所提出方法的复杂性。将线平均应用于平滑像素有助于控制算法的复杂性，