Wasserstein Distortion: Unifying Fidelity and Realism

Yang Qiu, Aaron B. Wagner, Johannes Ballé, Lucas Theis

Abstract: We introduce a distortion measure for images, Wasserstein distortion, that simultaneously generalizes pixel-level fidelity on the one hand and realism or perceptual quality on the other. We discuss its metric properties. Pairs of images that are close under Wasserstein distortion illustrate its utility. In particular, we generate random images that have high fidelity to a reference image in one location of the image and smoothly transition to an independent realization as one moves away from this point. Wasserstein distortion represents a generalization and synthesis of prior work on texture generation, image realism and distortion, and models of the early human visual system, in the form of an optimizable metric in the mathematical sense.