
Image colourisation by non‐local total variation method in the CB and YIQ colour spaces
Author(s) -
Hu Haibing,
Li Fang
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0489
Subject(s) - chromaticity , mathematics , brightness , lagrange multiplier , variation (astronomy) , grayscale , artificial intelligence , computer vision , computer science , image (mathematics) , mathematical optimization , optics , physics , astrophysics
Colourisation is a process of adding colour to greyscale images. In this study, the authors propose two new colourisation models based on non‐local total variation regularisation in the chromaticity and brightness (CB) colour space and the YIQ colour space. Lagrange multiplier method is used to handle the sphere constraint of chromaticity in the CB colour space. By introducing an extra variable and using the dual version of non‐local total variation, they split the proposed colourisation problems into two subproblems with closed‐form solutions and get two iterative algorithms. Experimental results and comparisons demonstrate that the advantage of the proposed methods is that they can preserve the colour edges better than the closely related existing methods, especially the total variation methods.