Computing Science, School of

Receive updates for this collection

Colourization of Dichromatic Images

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2018-09
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, Viénot, Mollon, JOSA A 14, 2647-2655, 1997).

Document type: 
Conference presentation
File(s): 

Colour Discrimination Ellipses Explained by Metamer Mismatching

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2018-09
Abstract: 

Many psychophysical experiments have shown that colour discrimination varies substantially with the region of colour space in which the colours reside. Many models of the experimental data have been proposed, and many uniform colour spaces have been developed that attempt to represent colour in a coordinate system such that equally discriminable colours are equal distances apart, but all of them are based on fits to the experimental data. Many provide good fits to the data, but they remain data models and do not explain why colour discrimination varies in the way it does. In contrast, this paper outlines a theory of colour discrimination based on the uncertainties reflected in the extent of metamer mismatching. The greater its extent, the more finely a colour needs to be discriminated.

Document type: 
Conference presentation
File(s): 

Spectral Gamut Mapping and Gamut Concavity

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2007-11
Abstract: 

A spectral gamut-mapping algorithm is introduced that works well for printers with a large number of inks. It finds the best mapping onto the convex hull of the printer spectral gamut while preserving color defined in CIE XYZ as much as possible. The technique employs a non-negative least-square fit. Since the gamut-mapping algorithm depends on the common assumption that the gamut is convex, an experimental study of the degree of gamut concavity is conducted. It finds that there is a significant amount of concavity, and that that the degree does not appear to change much as the number of inks is increased. Finally, the performance of the gamut-mapping algorithm and gamut coverage in spectral space is compared for 3-, 4-, 5- and 6-ink printers using both synthetic ink models and real ink data.

Document type: 
Conference presentation
File(s): 

Luminance-Based Multi-Scale Retinex

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
1997-05
Abstract: 

Multi-scale retinex (MSR) processing has been shown to be an effective way to enhance image contrast, but it often has an undesirable desaturating effect on the image colours. A colourrestoration method [2,3]can help mitigate this effect, but our experience is that it simply leads to other problems. In this paper we modify MSR so that it preserves colour fidelity while still enhancing contrast. We then add neural-net based colour constancy processing[7] to this modified version of MSR. The result is a principled approach that provides the contrastenhancement benefits of MSR and improved colour fidelity.

Document type: 
Conference presentation
File(s): 

Investigations into Multi-Scale Retinex

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
1998-03
Abstract: 

The main thrust of this paper is to investigate the multi-scale retinex (MSR) approach to image enhancement to explain the effect of the processing from a theoretical standpoint. This leads to a new algorithm with fewer arbitrary parameters that is more flexible, maintains colour fidelity, and still preserves the contrast-enhancement benfits of the original MSR method. To accomplish this we identify the explicit and implicit processing goals of MSR. By decoupling the MSR operations from one another, we build an algorithm composed of independent steps that separates out the issues of gamma adjustment, colour balance, dynamic range compression, and colour enhancement, which are all jumbled together in the original MSR method. We then extend MSR with colour constancy and chromaticity-preserving contrast enhancement.

Document type: 
Conference presentation
File(s): 

Failure of Luminance-Redness Correlation for Illuminant Estimation

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2004-11
Abstract: 

We investigate the hypothesis, recently published in Nature, that the human visual system may use some sort of luminance-redness correlation2 together with the scene average for illuminant estimation. We found this idea interesting but not thoroughly tested. In particular, tests on real images were limited to scenes made up artificially from hyperspectral data,4 spectral power distributions of various daylight illuminants, and the human cone sensitivity functions. The Ruderman database4 of hyperspectral images is also quite peculiar because it consists of a small number of images of mostly foliage. Our experiments show that for scenes composed from a more diversified hyperspectral database combined with real illuminant spectra, the predicted correlation turns out to be very weak. For actual digital camera images, the luminance-redness correlation fails completely.

Document type: 
Conference presentation
File(s): 

Illumination Estimation using a Multilinear Constraint on Dichromatic Planes

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2005-09
Abstract: 

A new multilinear constraint on the color of the scene illuminant based on the dichromatic reflection model is proposed. The formulation avoids the problem, common to previous dichromatic methods, of having to first identify pixels corresponding to the same surface material. Once pixels from two or more materials have been identified, their corresponding dichromatic planes can be intersected to yield the illuminant color. However, it is not always easy to determine which pixels from an arbitrary region of an image belong to which dichromatic plane. The image region may cover an area of the scene encompassing several different materials and hence pixels from several different dichromatic planes. The new multilinear constraint accounts for this multiplicity of materials and provides a mechanism for choosing the most plausible illuminant from a finite set of candidate illuminants. The performance of this new method is tested on a database of real images.

Document type: 
Conference presentation
File(s): 

Independent Component Analysis and Nonnegative Linear Model Analysis of Illuminant and Reflectance Spectra

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2005-05
Abstract: 

Principal Component Analysis (PCA), Independent Component Analysis (ICA), Non-Negative Matrix Factorization (NNMF) and Non-Negative Independent Component Analysis (NNICA) are all techniques that can be used to compute basis vectors for finite-dimensional models of spectra. The two non-negative techniques turn out to be especially interesting because the pseudo-inverse of their basis vectors is also close to being non-negative. This means that after truncating any negative components of the pseudo-inverse vectors to zero, the resulting vectors become physically realizable sensors functions whose outputs map directly to the appropriate finite-dimensional weighting coefficients in terms of the associated (NNMF or NNICA) basis. Experiments show that truncating the negative values incurs only a very slight performance penalty in terms of the accuracy with which the input spectrum can be approximated using a finite-dimensional model.

Document type: 
Conference presentation
File(s): 

A Basis for Cones

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2006-01
Abstract: 

Why do the human cones have the spectral sensitivities they do? We hypothesize that they may have evolved to their present form because their sensitivities are optimal in terms of their ability to recover the spectrum of incident light. As evidence in favor of this hypothesis, we compare the accuracy with which the incoming spectrum can be approximated by a three-dimensional linear model based on the cone responses and compare this to the optimal approximations defined by models based on principal components analysis, independent component analysis, non-negative matrix factorization and non-negative independent component analysis. We introduce a new method of reconstructing spectra from the cone responses and show that the cones are almost as good as these optimal methods in estimating the spectrum.

Document type: 
Conference presentation
File(s): 

Multispectral Colour Constancy

Peer reviewed: 
Yes, item is peer reviewed.
Date created: 
2006-11
Abstract: 

Does extending the number of channels from the 3 RGB sensors of a colour camera to 6 or 9 using a multispectral camera enhance the performance of illumination-estimation algorithms? Experiments are conducted with a variety of colour constancy algorithms (Maloney-Wandell, Chromagenic, Greyworld, Max RGB, and a Maloney-Wandell extension) measuring their performance as a function of the number of sensor channels. Although minor improvements were found with 6 channels, overall the results indicate that multispectral imagery is unlikely to lead to substantially better illumination-estimation performance.

Document type: 
Conference presentation
File(s):