Spectral Color Research
Traditional color science has been dominated by the models of human
color vision. These models assume a three dimensional representation of
all colors. In addition to the color research, this three dimensional
approach is dominant in the standard technical realizations of color
measurement, imaging, and display. Some of the most common coordinate
systems are RGB and Lab color coordinate systems.
It has turned out that this traditional approach of three dimensional
color management is not sufficient in general color science nor in many
applications. This is true for point color measurements and as well as
A new emerging technology, spectral imaging, is developing rapidly for
needs of accurate color measurement, analysis, and digital color
management. This spectral approach makes it possible to e.g. avoid a
common problem of metamerism (two colors look the same under certain
illumination, but different under another) or compute a real colors of
an object under different illuminations.
This spectral approach to color is developing not only in theory, but
also technically. At the moment there are commercially available
spectral cameras and on laboratory level both multiprimary video cameras
and multiprimary displays. The memory requirements for raw images are
very high for spectral images. A comparative list of raw image file
sizes are shown below. Each component is assumed to require one byte.
256x256 pixels 512x512 pixels Grey-level image 66 kB 262 kB
color (RGB-) image 197 kB 786 kB
spectral, 20 nm resol. 1 MB 4 MB
spectral, 5 nm resol. 4 MB 16 MB
One can easily see that an efficient use of the spectral images requires
efficient compression and processing methods.
The use of spectral color analysis and spectral images is increasing
also in many applications. This is due to the rapidly developing
techniques. The applications include on-line paper color monitoring,
digital archives of paintings, food and plant quality control, quality
control in plastic industry, and real color reproduction in e-commerce.
In this tutorial course, the basics of spectral color science will be
given and methods for spectral image analysis and compression will be
studied. Also, there will be an overview to the present application
fields. The course include demonstrations to show the need of color
management, hands-on exercises where we take some spectral images, do
some analysis, and modify them to look realistic under different
an introductory material for the course. The tutorial
material include electronic copies of the lecture notes and some sample
spectral images for self study after the course.
is a professor and the Head of Department of Computer Science at the
University of Joensuu, Finland. He specializes in spectral color image
analysis, pattern recognition and molecular computing. He received his
B.Sc. in physics in 1979, his M.Sc. in medical physics in 1982 and his
Ph.D. in mathematics in 1989, all from the University of Kuopio, Finland.
In 1989-1990 he was a visiting researcher at The University of Iowa, IA,
USA, in 1990 a visiting professor at the University of Saskatchewan,
Canada, in 1991-1992 professor and the Head of Department of Computer
Science in the University of Kuopio, Finland, and in 1992-1998 professor
of Information Processing, in 1995-1998 dean of the Deapartment of
Information Technology at the Lappeenranta University of Technology,
Finland. In 1995-1999 he was the chairman of the Finnish Pattern
Recognition Society and he is a fellow and a member of the governing
board of the International Association of Pattern Recognition (IAPR).
He is the chairman of the CIE TC8-07 technical committee on Multispectral