Although spectral images contain large amount of information, compared with color images, the image acquisition is affected by several factors such as shading and specular highlight. Many researchers have introduced color invariant and spectral invariant representations for these factors using the standard dichromatic reflection model of inhomogeneous dielectric materials. However, these representations are inadequate for other materials like metal. This paper proposes a more general spectral invariant representation for obtaining reliable spectral reflectance images. Our invariant representation is derived from the standard dichromatic reflection model for dielectric materials and the extended dichromatic reflection model for metals. We proof the invariant formulas for spectral images of most natural objects preserve spectral information and are invariant to highlights, shading, surface geometry, and illumination intensity. The method is applied to the problem of material classification and image segmentation of a raw circuit board. Experiments are done with real spectral images to examine the performance of the proposed method.