Title: Pixel classified colourisation method based on neighbourhood similarity priori

Authors: Jie Chen; Zongliang Gan; Xiuchang Zhu; Jin Wang

Addresses: Jiangsu Province Key Lab on Image Processing and Image Communication, Nanjing University of Post and Telecommunications, P.O. Box 166, No. 66 Xin Mofan Road, Nanjing, Jiangsu, China ' Jiangsu Province Key Lab on Image Processing and Image Communication, Nanjing University of Post and Telecommunications, P.O. Box 166, No. 66 Xin Mofan Road, Nanjing, Jiangsu, China ' Jiangsu Province Key Lab on Image Processing and Image Communication, Nanjing University of Post and Telecommunications, P.O. Box 166, No. 66 Xin Mofan Road, Nanjing, Jiangsu, China ' College of Information Engineering, Yangzhou University, No. 88 South University Ave, Yangzhou, Jiangsu, China

Abstract: Colourisation is a kind of computer-aided technology which automatically adds colours to greyscale images. This paper presents a scribble-based colourisation method which treats the flat and edge pixels differently. First, we classify the pixels to flat or edge pixel categories using the neighbourhood similarity pixels searching algorithm. Then, we compute the weighted coefficients of the edge pixels by solving a constraint quadratic programming problem and compute the weighted coefficients of the flat pixels based on their luminance distances. Finally, we transmit the weighted coefficients to the chrominance images according to the joint correlation property between luminance and chrominance channels, and combine with the colours scribbled on by the user to compute all the unknown colours. The experimental results show that our method is effective especially on reducing colour bleeding in the boundary parts and can give better results when only a few colours are scribbled on.

Keywords: colourisation; joint correlation; linear weighted combination; quadratic programming; active set; neighbourhood similarity pixels.

DOI: 10.1504/IJHPCN.2018.094945

International Journal of High Performance Computing and Networking, 2018 Vol.12 No.3, pp.270 - 277

Received: 10 Mar 2016
Accepted: 24 Aug 2016
Published online: 28 Sep 2018 *

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