A set of multichannel camera systems and algorithms is described for recovering both the surface spectral-reflectance function and the illuminant spectral-power distribution from the data of spectral imaging. We describe a camera system with six spectral channels of fixed wavelength bands. This system is composed of a monochrome charge-coupled device camera, six different color filters, and a personal computer. The dynamic range of the camera is extended for sensing the high-intensity levels of highlights. We assume that the object surfaces in a scene are made of an inhomogeneous dielectric material whose reflection properties are described by the dichromatic reflection model. The process for estimating the spectral data comprises several steps: (1) finitedimensional linear model representation of wavelength functions, (2) illuminant estimation, (3) data normalization and image segmentation, and (4) reflectance estimation. An algorithm is proposed for detecting highlight areas in the image. The reliability of the camera system and the algorithms is demonstrated in an experiment. Finally, a new type of camera system using a liquid-crystal filter is proposed.