Paper
8 February 2015 Spatial Intensity Channel Replacement Daltonization (SIChaRDa)
Joschua Thomas Simon-Liedtke, Ivar Farup
Author Affiliations +
Proceedings Volume 9395, Color Imaging XX: Displaying, Processing, Hardcopy, and Applications; 939516 (2015) https://doi.org/10.1117/12.2079226
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
Color-deficient observers are often confronted with problems in daily life due to the fact that some colors appear less differentiable than for normal sighted people. So-called daltonization methods have been proposed to increase color contrast for color-deficient people. We propose two methods for better daltonization solutions by Spatial Intensity Channel Replacement Daltonization (SIChaRDa). We propose replacing the intensity channel with a grayscale version of the image computed by using spatial color-to-gray methods that are either capable of translating color contrasts into lightness contrasts or that are capable of translating color edges into lightness edges, and/or integrating information from the red–green channel into the intensity channel. We tested two implementations on different types of images, and we could show that results depend on the one hand on the algorithm used for computing the grayscale image, and on the other hand on the content of the image. We show that the spatial methods work best on real-life images were confusing colors are directly adjacent to each other, respectively where they are in close proximity. On the contrary, using composed artificial images with borders of white space between colors – like for example in the Ishihara plates – leads only to unsatisfactory results.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joschua Thomas Simon-Liedtke and Ivar Farup "Spatial Intensity Channel Replacement Daltonization (SIChaRDa)", Proc. SPIE 9395, Color Imaging XX: Displaying, Processing, Hardcopy, and Applications, 939516 (8 February 2015); https://doi.org/10.1117/12.2079226
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
RGB color model

Image quality

Visualization

Image enhancement

Visual system

Image processing

Information visualization

Back to Top