Colourization of Dichromatic Images

Peer reviewed: 
Yes, item is peer reviewed.
Scholarly level: 
Faculty/Staff
Final version published as: 

Funt, B., and Zhu, L., "Colourization of Dichromatic Images," Proc. AIC 2018 International Colour Association Conference, Lisbon. Sept. 2018.

Date created: 
2018-09
Keywords: 
Colour blindness
Dichromat
Computational colour vision
Colourization
Abstract: 

This paper explores the colour information dichromatic vision provides in terms of its potential for colourization. Given a greyscale image as input, colourization generates an RGB image as output. Since colourization works well for luminance images, how well they might work for dichromatic images? Dichromatic images are colourized using a modification of the colourization method of Iizuka et al. (Proc. SIGGRAPH 2016, 35(4):110:1-110:11). In particular, an sRGB image is converted to cone LMS and M is discarded to yield a LS image. During training, the colourization neural network is provided LS images and their corresponding LMS images, and it adjusts its weights so that M is predicted from the L and S. One does not easily recognize that a colourized dichromatic image is, in fact, based on only L and S, and is not a regular full-colour image. This is stark contrast to the dichromatic simulations of Brettel et al. (Brettel, ViƩnot, Mollon, JOSA A 14, 2647-2655, 1997).

Description: 

Presented at the 2018 AIC Congress, Lisbon, Portugal, 25-29 September 2018.

Language: 
English
Document type: 
Conference presentation
Rights: 
Rights remain with the authors.
File(s): 
Sponsor(s): 
Natural Sciences and Engineering Research Council of Canada (NSERC)
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