Transferring Colours to Grayscale Images by Locally Linear Embedding
Author(s) -
Jun Li,
Pengwei Hao,
Chengqi Zhang
Publication year - 2008
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.22.83
Subject(s) - grayscale , computer science , artificial intelligence , chromatic scale , embedding , computer vision , image (mathematics) , contrast (vision) , pattern recognition (psychology) , mathematics , combinatorics
In this paper, we propose a learning-based method for adding colours to grayscale images. In contrast to many previous computer-aided colourizing methods, which require intensive and accurate human intervention, our method needs only the user to provide a colourful image of the similar content as the grayscale image. We accept the “image manifold” assumption and apply manifold learning methods to model the relations between the chromatic channels and the gray levels in the training images. Then we synthesize the objective chromatic channels using the learned relations. Experiments show that our method gives superior results to those of the previo us work.
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