We introduce a distortion measure for images, Wasserstein distortion, that simultaneously generalizes pixel-level fidelity on the one hand and realism on the other. We show how Wasserstein distortion reduces mathematically to a pure fidelity constraint or a pure realism constraint under different parameter choices. Pairs of images that are close under Wasserstein distortion illustrate its utility. In particular, we generate random textures that have high fidelity to a reference texture in one location of the image and smoothly transition to an independent realization of the texture as one moves away from this point. Connections between Wasserstein distortion and models of the human visual system are noted.

翻译：我们提出一种图像失真度量——Wasserstein失真，它同时泛化了像素级保真度与图像真实感。我们展示了Wasserstein失真如何在不同的参数选择下，在数学上简化为纯粹的保真度约束或纯粹的真实感约束。在Wasserstein失真度量下相近的图像对验证了其有效性。具体而言，我们生成随机纹理，这些纹理在图像某一位置对参考纹理具有高保真度，并随着远离该点平滑过渡为纹理的独立实现。我们还指出了Wasserstein失真与人类视觉系统模型之间的关联。