JOURNAL ARTICLE

Image completion with structure propagation

Jian SunLu YuanJiaya JiaHeung‐Yeung Shum

Year: 2005 Journal:   ACM Transactions on Graphics Vol: 24 (3)Pages: 861-868   Publisher: Association for Computing Machinery

Abstract

In this paper, we introduce a novel approach to image completion, which we call structure propagation. In our system, the user manually specifies important missing structure information by extending a few curves or line segments from the known to the unknown regions. Our approach synthesizes image patches along these user-specified curves in the unknown region using patches selected around the curves in the known region. Structure propagation is formulated as a global optimization problem by enforcing structure and consistency constraints. If only a single curve is specified, structure propagation is solved using Dynamic Programming. When multiple intersecting curves are specified, we adopt the Belief Propagation algorithm to find the optimal patches. After completing structure propagation, we fill in the remaining unknown regions using patch-based texture synthesis. We show that our approach works well on a number of examples that are challenging to state-of-the-art techniques.

Keywords:
Computer science Consistency (knowledge bases) Local consistency Algorithm Image (mathematics) Texture (cosmology) Line (geometry) Mathematical optimization Theoretical computer science Artificial intelligence Mathematics Geometry

Metrics

536
Cited By
25.76
FWCI (Field Weighted Citation Impact)
41
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Generative Adversarial Networks and Image Synthesis
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Computer Graphics and Visualization Techniques
Physical Sciences →  Computer Science →  Computer Graphics and Computer-Aided Design
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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