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Image interpolation, or image morphing, refers to a visual transition betweentwo (or more) input images. For such a transition to look visually appealing,its desirable properties are (i) to be smooth; (ii) to apply the minimalrequired change in the image; and (iii) to seem "real", avoiding unnaturalartifacts in each image in the transition. To obtain a smooth andstraightforward transition, one may adopt the well-known Wasserstein BarycenterProblem (WBP). While this approach guarantees minimal changes under theWasserstein metric, the resulting images might seem unnatural. In this work, wepropose a novel approach for image morphing that possesses all three desiredproperties. To this end, we define a constrained variant of the WBP thatenforces the intermediate images to satisfy an image prior. We describe analgorithm that solves this problem and demonstrate it using the sparse priorand generative adversarial networks.

Barycenters of Natural Images -- Constrained Wasserstein Barycenters for Image Morphing