The goal of the work reported in this dissertation is to develop methods for the acquisition and reproduction of high quality digital color images. To reach this goal it is necessary to understand and control the way in which the different devices involved in the entire color imaging chain treat colors. Therefore we addressed the problem of colorimetric characterization of scanners and printers, providing efficient and colorimetrically accurate means of conversion between a device-independent color space such as the CIELAB space, and the device-dependent color spaces of a scanner and a printer. First, we propose a new method for the colorimetric characterization of color scanners. It consists of applying a non-linear correction to the scanner RGB values followed by a 3rd order 3D polynomial regression function directly to CIELAB space. This method gives very good results in terms of residual color differences. The method has been successfully applied to several color image acquisition devices, including digital cameras. Together with other proposed algorithms for image quality enhancements it has allowed us to obtain very high quality digital color images of fine art paintings. An original method for the colorimetric characterization of a printer is then proposed. The method is based on a computational geometry approach. It uses a 3D triangulation technique to build a tetrahedral partition of the printer color gamut volume and it generates a surrounding structure enclosing the definition domain. The characterization provides the inverse transformation from the device-independent color space CIELAB to the device-dependent color space CMY, taking into account both colorimetric properties of the printer, and color gamut mapping. To further improve the color precision and color fidelity we have per-formed another study concerning the acquisition of multispectral images using a monochrome digital camera together with a set of K >3 carefully selected color filters. Severa
