As long as the colors are found to be approximatively as expected, people are generally happy with their images. However, with the increased use of color images, people's quality requirements also have increased considerably. Just a few years ago, a computer graphics system capable of producing 256 different colors was more than enough for most users, while today, most computers that are sold have true color capabilities, being able to produce 16.7 million colors.
Furthermore, several professions have particular needs for high-quality color images. Artists are very concerned about colors in their works, and so are the art historians and curators studying their works. The printing, graphic arts, and photography industries have been concerned about color imaging for a long time. Most of the color imaging standards and equipment used today have their roots in these industries. But the past twenty years have seen the field of digital color imaging emerging from specialised scientific applications into the mainstream of computing. Color is also extremely important in several other fields, such as the textile and clothing industry, automotive industry, decoration and architecture.
Digital color imaging systems process electronic information from various sources: images may come from the Internet, a remote sensing device, a local scanner, etc. After processing, a document is usually compressed and transmitted to several places via a computer network for viewing, editing or printing. To achieve color consistency throughout such a widely distributed system, it is necessary to understand and control the way in which the different devices involved in the entire color imaging chain treat colors. Each scanner, monitor, printer, or other color imaging device, senses or displays color in a different, device-dependent, way. One approach to exchanging images between these devices is to calibrate each color image acquisition and reproduction device to a device-independent color space. The exchange of images can then be done in this color space, which should conform to international standards.
However, colors represent an important but nevertheless limited aspect of the objects that surround us. They correspond to the human perception of its surface under given light conditions. For the needs of, for example, an art curator wanting to control any changes or ageing of the materials in a fine arts painting, or a publisher wanting extra high-fidelity color reproduction, it becomes necessary to provide a more complete spectral analysis of the objects. This requires technology and devices capable of acquiring multispectral images. A multispectral image may also be used to reproduce an image of the object as it would have appeared under a given illuminant.
In my research, I have investigated several of the aspects mentioned above. I have developed novel algorithms for the colorimetric characterisation of scanners and printers providing efficient and colorimetrically accurate means of conversion between a device-independent color space such as CIELAB, and the device-dependent color spaces of a scanner and a printer. Furthermore, I have developed algorithms for multispectral image capture using a CCD camera with carefully selected optical filters. The developed algorithms have been used for several applications, such as fine-arts archiving and color facsimile.