Image inpainting based on energy minimization

Abstract

Image inpainting techniques have been widely used to remove undesired visual objects in images such as damaged portions of photographs and people who have accidentally entered into pictures. Conventionally, the missing parts of an image are completed by optimizing the objective function which is defined based on the sum of SSD (sum of squared differences). However, the naive SSD-based objective function is not robust against intensity change in an image. Thus, unnatural intensity change often appears in the missing parts. In addition, when an image has continuously changing texture patterns, the completed texture in a resultant image sometimes blurs due to inappropriate pattern matching. In this paper, in order to improve the image quality of the completed texture, the conventional objective function is newly extended by considering intensity changes and spatial locality to prevent unnatural intensity changes and blurs in a resultant image. By minimizing the extended energy function, the missing regions can be completed without unnatural intensity changes and blurs. In experiments, the effectiveness of the proposed method is successfully demonstrated by applying our method to various images and comparing the results with those obtained by the conventional method.