Image restoration using content-adaptive mesh modeling

Abstract

In this work we explore the use of a content-adaptive mesh model (CAMM) in the classical problem of image restoration. In the proposed framework, we first model the image to be restored by an efficient mesh representation. A CAMM can be viewed as a form of image representation using nonuniform samples, of which the mesh nodes (i.e., image samples) are adaptively placed according to the local content of the image. The image is then restored through estimating the model parameters (i.e., mesh nodal values) from the data. A CAMM provides a natural spatially-adaptive regularization mechanism for image restoration in that the interpolation basis functions in a CAMM have their spatial support varying with the local image content. We present some exploratory results to demonstrate the proposed approach.