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Cluster Computing
Published in: Cluster Computing 3/2019

28-03-2018

The research of image inpainting algorithm using self-adaptive group structure and sparse representation

Authors: Jiangchun Mo, Yucai Zhou

Published in: Cluster Computing | Special Issue 3/2019

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Abstract

Focused on the issue that the object structure discontinuity and poor texture detail occurred in image inpainting method, the image inpainting algorithm based on self-adaptive group structure has proposed in this paper. The conception of self-adaptive group structure is different from traditional image patching operation and fixed group structure, which refers to the fact that a patch on the structure has fewer similar patches than the one within the textured region. A self-adaptive dictionary as well as the sparse representation model was established in the domain of self-adaptive group. Finally, the target cost function was solved by Split Bregman Iterational operation. The experimental results on target removing with Criminisi’s algorithm, GSR’s algorithm and SALSA’s algorithm in image pixels losting of image inpainting had shown that the proposed algorithm has better performance than other algorithms.
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Metadata
Title
The research of image inpainting algorithm using self-adaptive group structure and sparse representation
Authors
Jiangchun Mo
Yucai Zhou
Publication date
28-03-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2323-8

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