A computational framework for colour metrics and colour space transforms

An object-oriented computational framework for the transformation of colour data and colour metric tensors is presented. The main idea of the design is to represent the transforms between spaces as compositions of objects from a class hierarchy providing the methods for both the transforms themselves and the corresponding Jacobian matrices. In this way, new colour spaces can be implemented on the fly by transforming from any existing colour space, and colour data in various formats as well as colour metric tensors and colour difference data can easily be transformed between the colour spaces. This reduces what normally requires several days of coding to a few lines of code without introducing a significant computational overhead. The framework is implemented in the Python programming language.

[1]  D. L. Macadam.  Visual Sensitivities to Color Differences in Daylight , 1942 .

[2]  G. vanRossum.  Python reference manual , 1995 .

[3]  I. Farup.  Hyperbolic geometry for colour metrics. , 2014, Optics express.

[4]  Reiner Lenz,et al.  The Hyperbolic Geometry of Illumination-Induced Chromaticity Changes , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Changjun Li,et al.  The CIECAM02 Color Appearance Model , 2002, CIC.

[6]  Analysis of Three Euclidean Color-Difference Formulas for Predicting the Average RIT-DuPont Color-Difference Ellipsoids , 2013 .

[7]  M. Luo,et al.  The development of the CIE 2000 Colour Difference Formula , 2001 .

[8]  Juliane Junker,et al.  Color Image Processing And Applications , 2016 .

[9]  Guihua Cui,et al.  Measurement of the relationship between perceived and computed color differences. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[10]  Ali Alsam,et al.  Colour Gamut Mapping as a Constrained Variational Problem , 2009, SCIA.

[11]  Dibakar R. Pant,et al.  Riemannian formulation and comparison of color difference formulas , 2012 .

[12]  Jon Yngve Hardeberg,et al.  Evaluation of Algorithms for the Determination of Color Gamut Boundaries , 2010 .

[13]  Travis E. Oliphant,et al.  Guide to NumPy , 2015 .

[14]  Mark D. Fairchild,et al.  Development and Testing of a Color Space (IPT) with Improved Hue Uniformity , 1998, CIC.

[15]  Xing Cai,et al.  On the performance of the Python programming language for serial and parallel scientific computations , 2005, Sci. Program..

[16]  Dibakar R. Pant,et al.  Geodesic calculation of color difference formulas and comparison with the munsell color order system , 2013 .

[17]  Mark S. Shephard,et al.  An Object-Oriented Framework for Reliable Numerical Simulations , 1999, Engineering with Computers.

[18]  Guihua Cui,et al.  Uniform colour spaces based on the DIN99 colour‐difference formula , 2002 .

[19]  W D Wright,et al.  Color Science, Concepts and Methods. Quantitative Data and Formulas , 1967 .

[20]  Elena Deza,et al.  Encyclopedia of Distances , 2014 .

[21]  Ed Anderson,et al.  LAPACK Users' Guide , 1995 .

[22]  Rafael Huertas,et al.  Euclidean color-difference formula for small-medium color differences in log-compressed OSA-UCS space. , 2009, Journal of the Optical Society of America. A, Optics, image science, and vision.