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Erschienen in: Cluster Computing 6/2019

01.03.2018

Damaged region filling by improved criminisi image inpainting algorithm for thangka

verfasst von: Fan Yao

Erschienen in: Cluster Computing | Sonderheft 6/2019

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Abstract

In order to solve the problems of the criminisi algorithm in inpainting thangka image, such as the mistake matching phenomenon, image structure information inconsistent and the inaccurate matching standards, the new image inpainting algorithm based on thangka image structure information is proposed in this paper. The following three steps are the keys of this method. (1) The correlation of repaired block and its neighborhood block is introduced and the priority of formula is improved; (2) The exemplar-based size selection is improved, the adaptive patch size is automatically adjusted according to the exemplar-based information changes; (3) In order to solve mistake matching problem, the structure information of thangka image and color of Euclidean distance are combined as the new matching criterion. The experimental results show that the mistake matching phenomenon by the proposed method for thangka image is significantly reduced, the structure of thangka image is more fluent and smooth than them in comparative literature.

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Metadaten
Titel
Damaged region filling by improved criminisi image inpainting algorithm for thangka
verfasst von
Fan Yao
Publikationsdatum
01.03.2018
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 6/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2068-4

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