Abstract
Image inpainting is a tequnique for removing undesired visual objects in images and filling the missing regions with plausible textures. Conventionally, the missing parts of an image are completed by optimizing the objective function, which is defined based on pattern similarity between the missing region and the rest of the image (data region). However, unnatural textures are easily generated due to two factors: (1) available samples in the data region are quite limited, and (2) pattern similarity is one of the required conditions but is not sufficient for reproducing natural textures. In this paper, in order to improve the image quality of completed texture, the objective function is extended by allowing brightness changes of sample textures (for (1)) and introducing spatial locality as an additional constraint (for (2)). The effectiveness of these extensions is successfully demonstrated by applying the proposed method to one hundred images and comparing the results with those obtained by the conventional methods.
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