The Relation between Color Spaces and Compositional Data Analysis Demonstrated with Magnetic Resonance Image Processing Applications

Abstract

This paper presents a novel application of compositional data analysis methods in the context of color image processing. A vector decomposition method is proposed to reveal compositional components of any vector with positive components followed by compositional data analysis to demonstrate the relation between color space concepts such as hue and saturation to their compositional counterparts. The proposed methods are applied to a magnetic resonance imaging dataset acquired from a living human brain and a digital color photograph to perform image fusion. Potential future applications in magnetic resonance imaging are mentioned and the benefits/disadvantages of the proposed methods are discussed in terms of color image processing.

Author Biography

Omer Faruk Gulban, Maastricht University

Department of Cognitive Neuroscience

PhD Student

References

De Martino, F., Moerel, M., Xu, J., van de Moortele, P.-F., Ugurbil, K., Goebel, R., Yacoub, E., Formisano, E. (2014). High-Resolution Mapping of Myeloarchitecture In Vivo: Localization of Auditory Areas in the Human Brain. Cerebral Cortex, 25 (10), 3394-405.

Glasser, M. F., Van Essen, D. C. (2011). Mapping human cortical areas in vivo based on myelin content as revealed by T1- and T2-weighted MRI. Journal of Neuroscience, 31 (32), 11597-616.

Helms, G. (2016). Segmentation of human brain using structural MRI. Magnetic Resonance Materials in Physics, Biology and Medicine, 29 (2), 111-124.

James, A. P., Dasarathy, B. V. (2014). Medical image fusion: A survey of the state of the art. Information Fusion, 19 (1), 4-19.

Levkowitz, H., Herman, G.T. (1993). GLHS: A Generalized Lightness, Hue, and Saturation Color Model. CVGIP: Graphical Models and Image Processing, 55 (4), 271-285.

Pawlowsky-Glahn, V., Egozcue, J. J., Tolosana-Delgado, R. (2015). Modelling and Analysis of Compositional Data. Chichester, UK: John Wiley & Sons, Ltd.

Pohl, C., van Genderen, J. (2016). Remote Sensing Image Fusion. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press

Smith, A. R. (1978). Color gamut transform pairs. ACM SIGGRAPH Computer Graphics, 12(3), 12-19.

Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17 (3), 143-155.

Ugurbil, K. (2014). Magnetic Resonance Imaging at Ultrahigh Fields. IEEE Transactions on Biomedical Engineering, 61 (5), 1364-1379.

Van de Moortele, P.-F., Auerbach, E. J., Olman, C., Yacoub, E., Ugurbil, K., Moeller, S. (2009). T1 weighted brain images at 7 Tesla unbiased for Proton Density, T2* contrast and RF coil receive B1 sensitivity with simultaneous vessel visualization. NeuroImage, 46 (2), 432-46.

Published
2018-09-08
How to Cite
Gulban, O. F. (2018). The Relation between Color Spaces and Compositional Data Analysis Demonstrated with Magnetic Resonance Image Processing Applications. Austrian Journal of Statistics, 47(5), 34-46. https://doi.org/10.17713/ajs.v47i5.743
Section
CoDaWork 2017