IEEE Trans Image Process - Hierarchical super-resolution-based inpainting.

Tópicos

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Resumo

This paper introduces a novel framework for examplar-based inpainting. It consists in performing first the inpainting on a coarse version of the input image. A hierarchical super-resolution algorithm is then used to recover details on the missing areas. The advantage of this approach is that it is easier to inpaint low-resolution pictures than high-resolution ones. The gain is both in terms of computational complexity and visual quality. However, to be less sensitive to the parameter setting of the inpainting method, the low-resolution input picture is inpainted several times with different configurations. Results are efficiently combined with a loopy belief propagation and details are recovered by a single-image super-resolution algorithm. Experimental results in a context of image editing and texture synthesis demonstrate the effectiveness of the proposed method. Results are compared to five state-of-the-art inpainting methods.

Resumo Limpo

paper introduc novel framework examplarbas inpaint consist perform first inpaint coars version input imag hierarch superresolut algorithm use recov detail miss area advantag approach easier inpaint lowresolut pictur highresolut one gain term comput complex visual qualiti howev less sensit paramet set inpaint method lowresolut input pictur inpaint sever time differ configur result effici combin loopi belief propag detail recov singleimag superresolut algorithm experiment result context imag edit textur synthesi demonstr effect propos method result compar five stateoftheart inpaint method

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