Is the center position fully capable of representing a pixel? There is nothing wrong to represent pixels with their centers in a discrete image representation, but it makes more sense to consider each pixel as the aggregation of signals from a local area in an image super-resolution (SR) context. Despite the great capability of coordinate-based implicit representation in the field of arbitrary-scale image SR, this area's nature of pixels is not fully considered. To this end, we propose integrated positional encoding (IPE), extending traditional positional encoding by aggregating frequency information over the pixel area. We apply IPE to the state-of-the-art arbitrary-scale image super-resolution method: local implicit image function (LIIF), presenting IPE-LIIF. We show the effectiveness of IPE-LIIF by quantitative and qualitative evaluations, and further demonstrate the generalization ability of IPE to larger image scales and multiple implicit-based methods. Code will be released.

本文通过将频率信息聚合在像素区域中来扩展传统的位置编码，提出了集成位置编码（IPE），并将其应用于最先进的任意尺度图像超分辨率方法之一：局部隐式图像函数（LIIF），提出了IPE-LIIF。我们通过定量和定性评估展示了IPE-LIIF的有效性，进一步证明了IPE对更大的图像尺度和多个隐式方法的泛化能力。

综合位置编码增强图像超分辨率中的多尺度隐式学习