Digital image capture to faithfully record fine art paintings is a fundamental task in a cultural heritage domain which is increasingly benefiting from the possibilities afforded by computer systems and art databases. Indeed, the digital format greatly facilitates in the archiving, retrieval, and dissemination of art. Many museums, archives, and libraries have for some years been engaged in direct digital image capture of cultural heritage. Digital imaging also opens the door to new postprocessing applications for conservation or restoration, such as art digital diagnosis and virtual restoration of paintings. In this context, multispectral imaging has taken a prominent role—in the first instance, for generating high-fidelity color reproductions and, second, for their use as image spectrometers giving the spectral signature of each image element of the painting. This article offers a tutorial description of multispectral systems exemplified by the multispectral capture of the Mona Lisa by Leonardo da Vinci. This acquisition was performed at the Louvre Museum in Paris, France, in October 2004 and was an important achievement of the conservation restoration innovation systems for image capture and digital archiving to enhance training, education, and lifelong learning (CRISATEL) European Union project. This project was the latest in a series of pioneering projects on the digital acquisition of paintings which started with the visual art system for archiving and retrieval of images (VASARI) project in 1989. This article is based on an equation that models the multispectral acquisition of images. The main components of this equation are described. They correspond to the lighting conditions, the filters, the sensor sensitivity, and associated noise sources. Moreover, the optimization problems involved in the design of multispectral cameras, their calibration, and the processing of the obtained data are introduced within the same mathematical framework.