Modeling, Measuring, and Compensating Color Weak Vision
2016 (English)In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 25, no 6, 2587-2600 p.Article in journal (Refereed) PublishedText
We use methods from Riemann geometry to investigate transformations between the color spaces of color-normal and color-weak observers. The two main applications are the simulation of the perception of a color weak observer for a color-normal observer, and the compensation of color images in a way that a color-weak observer has approximately the same perception as a color-normal observer. The metrics in the color spaces of interest are characterized with the help of ellipsoids defined by the just-noticeable-differences between the colors which are measured with the help of color-matching experiments. The constructed mappings are the isometries of Riemann spaces that preserve the perceived color differences for both observers. Among the two approaches to build such an isometry, we introduce normal coordinates in Riemann spaces as a tool to construct a global color-weak compensation map. Compared with the previously used methods, this method is free from approximation errors due to local linearizations, and it avoids the problem of shifting locations of the origin of the local coordinate system. We analyze the variations of the Riemann metrics for different observers obtained from new color-matching experiments and describe three variations of the basic method. The performance of the methods is evaluated with the help of semantic differential tests.
Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2016. Vol. 25, no 6, 2587-2600 p.
Color vision; color weak; color transformations; Riemannian geometry; Riemann normal coordinates
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:liu:diva-128718DOI: 10.1109/TIP.2016.2539679ISI: 000375271700004PubMedID: 27046849OAI: oai:DiVA.org:liu-128718DiVA: diva2:933912
Funding Agencies|Japan Society for the Promotion of Science (JSPS) ; Institute of Science and Engineering, Chuo University; Swedish Research Council through a framework grant for the project Energy Minimization for Computational Cameras [2014-6227]; Swedish Foundation for Strategic Research [IIS11-0081]2016-06-072016-05-302016-08-31