Improved Color Constant Classification of Remotely Sensed Multispectral Imagery

For improved multispectral classification and retrieval of Lambertian reflectances from patches of arbitrary surface orientation, we investigate the consequences of a dichromatic illumination model accounting for direct sunlight and diffuse skylight. This illumination model leads to the concept of spectral classes as two dimensional planes in the feature space. This paper addresses three questions arising from this concept and applies them to experimental data: We presents the projected spectral angle as a novel spectral distance for the classification of multispectral images. We show how the normalized Lambertian reflectance of a surface can be retrieved from at least two observed spectra under arbitrary angles.