Morphological Amoeba-based Patches for Exemplar-Based Inpainting

2018 
Inpainting is the process of replacing areas in an image with a perceptually plausible substitution. A common technique is to iteratively match and fill small patches at the edge of the target region making use of similar patches from the same image. Nearly all inpainting algorithms based on this approach use a single patch size for the entire image. Yet, it seems clear that differently sized structures within the same image – for example a leaf versus a car tire – may require different patch sizes in order to achieve reasonable inpainting results. Likewise, a fixed patch size will give different results for the same image when the image resolution is doubled. A reasonable patch should therefore take into account the overall image size as well as the size and shape of the structures at the patch location. The aim of our paper is to study the effect of adaptively altering size and shape of the patch. We show that this technique leads to a better quality of the inpainting result compared to a fixed patch size.
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