Image colourisation using graph-based semi-supervised learning

B.-B. Liu; Z.-M. Lu

Image colourisation using graph-based semi-supervised learning

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Image colourisation using graph-based semi-supervised learning

Author(s): B.-B. Liu and Z.-M. Lu
DOI: 10.1049/iet-ipr.2008.0112

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Author(s): B.-B. Liu ¹ and Z.-M. Lu ¹
- Affiliations: 1: School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, People's Republic of China
Source: Volume 3, Issue 3, June 2009, p. 115 – 120
DOI: 10.1049/iet-ipr.2008.0112 , Print ISSN 1751-9659, Online ISSN 1751-9667

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A novel colourisation algorithm using graph-based semi-supervised learning (SSL) is presented. We show that the assumption of the colourisation problem is consistent with the fundamental of graph-based SSL methods. Satisfactory results are obtained in the experiments that validate the proposed algorithm. To reduce the time and memory requirements when dealing with large scale images, we further propose a two-stage speedup approach. Comparative results show that the computation complexity is dramatically reduced.

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